inla.models {INLA} | R Documentation

## Valid models in INLA

### Description

This page describe the models implemented in `inla`, divided into sections: latent, group, scopy, mix, link, predictor, hazard, likelihood, prior, wrapper, lp.scale.

### Usage

    inla.models()

### Value

Valid sections are: latent, group, scopy, mix, link, predictor, hazard, likelihood, prior, wrapper, lp.scale.

### 'latent'

Valid models in this section are:

Model 'linear'.
  Properties:
    doc =

      `⁠Alternative interface to an fixed effect⁠`

    constr =

      `⁠FALSE⁠`

    nrow.ncol =

      `⁠FALSE⁠`

    augmented =

      `⁠FALSE⁠`

    aug.factor =

      `⁠1⁠`

    aug.constr =

      `⁠NULL⁠`

    n.div.by =

      `⁠NULL⁠`

    n.required =

      `⁠FALSE⁠`

    set.default.values =

      `⁠FALSE⁠`

    pdf =

      `⁠linear⁠`

  Number of hyperparmeters is 0.

Model 'iid'.
  Properties:
    doc =

      `⁠Gaussian random effects in dim=1⁠`

    constr =

      `⁠FALSE⁠`

    nrow.ncol =

      `⁠FALSE⁠`

    augmented =

      `⁠FALSE⁠`

    aug.factor =

      `⁠1⁠`

    aug.constr =

      `⁠NULL⁠`

    n.div.by =

      `⁠NULL⁠`

    n.required =

      `⁠FALSE⁠`

    set.default.values =

      `⁠FALSE⁠`

    pdf =

      `⁠indep⁠`

  Number of hyperparmeters is 1.

  Hyperparameter 'theta'
    hyperid =

      `⁠1001⁠`

    name =

      `⁠log precision⁠`

    short.name =

      `⁠prec⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 5e-05⁠`

    initial =

      `⁠4⁠`

    fixed =

      `⁠FALSE⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

Model 'mec'.
  Properties:
    doc =

      `⁠Classical measurement error model⁠`

    constr =

      `⁠FALSE⁠`

    nrow.ncol =

      `⁠FALSE⁠`

    augmented =

      `⁠FALSE⁠`

    aug.factor =

      `⁠1⁠`

    aug.constr =

      `⁠NULL⁠`

    n.div.by =

      `⁠NULL⁠`

    n.required =

      `⁠FALSE⁠`

    set.default.values =

      `⁠FALSE⁠`

    pdf =

      `⁠mec⁠`

  Number of hyperparmeters is 4.

  Hyperparameter 'theta1'
    hyperid =

      `⁠2001⁠`

    name =

      `⁠beta⁠`

    short.name =

      `⁠b⁠`

    prior =

      `⁠gaussian⁠`

    param =

      `⁠1 0.001⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠2002⁠`

    name =

      `⁠prec.u⁠`

    short.name =

      `⁠prec⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 1e-04⁠`

    initial =

      `⁠9.21034037197618⁠`

    fixed =

      `⁠TRUE⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta3'
    hyperid =

      `⁠2003⁠`

    name =

      `⁠mean.x⁠`

    short.name =

      `⁠mu.x⁠`

    prior =

      `⁠gaussian⁠`

    param =

      `⁠0 1e-04⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠TRUE⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta4'
    hyperid =

      `⁠2004⁠`

    name =

      `⁠prec.x⁠`

    short.name =

      `⁠prec.x⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 10000⁠`

    initial =

      `⁠-9.21034037197618⁠`

    fixed =

      `⁠TRUE⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

Model 'meb'.
  Properties:
    doc =

      `⁠Berkson measurement error model⁠`

    constr =

      `⁠FALSE⁠`

    nrow.ncol =

      `⁠FALSE⁠`

    augmented =

      `⁠FALSE⁠`

    aug.factor =

      `⁠1⁠`

    aug.constr =

      `⁠NULL⁠`

    n.div.by =

      `⁠NULL⁠`

    n.required =

      `⁠FALSE⁠`

    set.default.values =

      `⁠FALSE⁠`

    pdf =

      `⁠meb⁠`

  Number of hyperparmeters is 2.

  Hyperparameter 'theta1'
    hyperid =

      `⁠3001⁠`

    name =

      `⁠beta⁠`

    short.name =

      `⁠b⁠`

    prior =

      `⁠gaussian⁠`

    param =

      `⁠1 0.001⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠3002⁠`

    name =

      `⁠prec.u⁠`

    short.name =

      `⁠prec⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 1e-04⁠`

    initial =

      `⁠6.90775527898214⁠`

    fixed =

      `⁠FALSE⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

Model 'rgeneric'.
  Properties:
    doc =

      `⁠Generic latent model specified using R⁠`

    constr =

      `⁠FALSE⁠`

    nrow.ncol =

      `⁠FALSE⁠`

    augmented =

      `⁠FALSE⁠`

    aug.factor =

      `⁠1⁠`

    aug.constr =

      `⁠NULL⁠`

    n.div.by =

      `⁠NULL⁠`

    n.required =

      `⁠TRUE⁠`

    set.default.values =

      `⁠TRUE⁠`

    pdf =

      `⁠rgeneric⁠`

  Number of hyperparmeters is 0.

Model 'cgeneric'.
  Properties:
    doc =

      `⁠Generic latent model specified using C⁠`

    constr =

      `⁠FALSE⁠`

    nrow.ncol =

      `⁠FALSE⁠`

    augmented =

      `⁠FALSE⁠`

    aug.factor =

      `⁠1⁠`

    aug.constr =

      `⁠NULL⁠`

    n.div.by =

      `⁠NULL⁠`

    n.required =

      `⁠TRUE⁠`

    set.default.values =

      `⁠TRUE⁠`

    pdf =

      `⁠rgeneric⁠`

  Number of hyperparmeters is 0.

Model 'rw1'.
  Properties:
    doc =

      `⁠Random walk of order 1⁠`

    constr =

      `⁠TRUE⁠`

    nrow.ncol =

      `⁠FALSE⁠`

    augmented =

      `⁠FALSE⁠`

    aug.factor =

      `⁠1⁠`

    aug.constr =

      `⁠NULL⁠`

    n.div.by =

      `⁠NULL⁠`

    n.required =

      `⁠FALSE⁠`

    set.default.values =

      `⁠FALSE⁠`

    min.diff =

      `⁠1e-08⁠`

    pdf =

      `⁠rw1⁠`

  Number of hyperparmeters is 1.

  Hyperparameter 'theta'
    hyperid =

      `⁠4001⁠`

    name =

      `⁠log precision⁠`

    short.name =

      `⁠prec⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 5e-05⁠`

    initial =

      `⁠4⁠`

    fixed =

      `⁠FALSE⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

Model 'rw2'.
  Properties:
    doc =

      `⁠Random walk of order 2⁠`

    constr =

      `⁠TRUE⁠`

    nrow.ncol =

      `⁠FALSE⁠`

    augmented =

      `⁠FALSE⁠`

    aug.factor =

      `⁠1⁠`

    aug.constr =

      `⁠NULL⁠`

    n.div.by =

      `⁠NULL⁠`

    n.required =

      `⁠FALSE⁠`

    set.default.values =

      `⁠FALSE⁠`

    min.diff =

      `⁠1e-08⁠`

    pdf =

      `⁠rw2⁠`

  Number of hyperparmeters is 1.

  Hyperparameter 'theta'
    hyperid =

      `⁠5001⁠`

    name =

      `⁠log precision⁠`

    short.name =

      `⁠prec⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 5e-05⁠`

    initial =

      `⁠4⁠`

    fixed =

      `⁠FALSE⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

Model 'crw2'.
  Properties:
    doc =

      `⁠Exact solution to the random walk of order 2⁠`

    constr =

      `⁠TRUE⁠`

    nrow.ncol =

      `⁠FALSE⁠`

    augmented =

      `⁠FALSE⁠`

    aug.factor =

      `⁠2⁠`

    aug.constr =

      `⁠1⁠`

    n.div.by =

      `⁠NULL⁠`

    n.required =

      `⁠FALSE⁠`

    set.default.values =

      `⁠FALSE⁠`

    min.diff =

      `⁠1e-08⁠`

    pdf =

      `⁠crw2⁠`

  Number of hyperparmeters is 1.

  Hyperparameter 'theta'
    hyperid =

      `⁠6001⁠`

    name =

      `⁠log precision⁠`

    short.name =

      `⁠prec⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 5e-05⁠`

    initial =

      `⁠4⁠`

    fixed =

      `⁠FALSE⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

Model 'prw2'.
  Properties:
    doc =

      `⁠Proper random walk of order 2⁠`

    constr =

      `⁠FALSE⁠`

    nrow.ncol =

      `⁠FALSE⁠`

    augmented =

      `⁠FALSE⁠`

    aug.factor =

      `⁠1⁠`

    aug.constr =

      `⁠NULL⁠`

    n.div.by =

      `⁠NULL⁠`

    n.required =

      `⁠FALSE⁠`

    set.default.values =

      `⁠FALSE⁠`

    pdf =

      `⁠prw2⁠`

  Number of hyperparmeters is 2.

  Hyperparameter 'theta1'
    hyperid =

      `⁠6103⁠`

    name =

      `⁠log precision⁠`

    short.name =

      `⁠prec⁠`

    prior =

      `⁠pc.prec⁠`

    param =

      `⁠1 0.01⁠`

    initial =

      `⁠4⁠`

    fixed =

      `⁠FALSE⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠6102⁠`

    name =

      `⁠log range⁠`

    short.name =

      `⁠range⁠`

    prior =

      `⁠pc.prw2.range⁠`

    param =

      `⁠0 0 0 0⁠`

    initial =

      `⁠3⁠`

    fixed =

      `⁠FALSE⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

Model 'seasonal'.
  Properties:
    doc =

      `⁠Seasonal model for time series⁠`

    constr =

      `⁠FALSE⁠`

    nrow.ncol =

      `⁠FALSE⁠`

    augmented =

      `⁠FALSE⁠`

    aug.factor =

      `⁠1⁠`

    aug.constr =

      `⁠NULL⁠`

    n.div.by =

      `⁠NULL⁠`

    n.required =

      `⁠FALSE⁠`

    set.default.values =

      `⁠FALSE⁠`

    missing.values.warning =

      `⁠TRUE⁠`

    pdf =

      `⁠seasonal⁠`

  Number of hyperparmeters is 1.

  Hyperparameter 'theta'
    hyperid =

      `⁠7001⁠`

    name =

      `⁠log precision⁠`

    short.name =

      `⁠prec⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 5e-05⁠`

    initial =

      `⁠4⁠`

    fixed =

      `⁠FALSE⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

Model 'besag'.
  Properties:
    doc =

      `⁠The Besag area model (CAR-model)⁠`

    constr =

      `⁠TRUE⁠`

    nrow.ncol =

      `⁠FALSE⁠`

    augmented =

      `⁠FALSE⁠`

    aug.factor =

      `⁠1⁠`

    aug.constr =

      `⁠NULL⁠`

    n.div.by =

      `⁠NULL⁠`

    n.required =

      `⁠TRUE⁠`

    set.default.values =

      `⁠TRUE⁠`

    pdf =

      `⁠besag⁠`

  Number of hyperparmeters is 1.

  Hyperparameter 'theta'
    hyperid =

      `⁠8001⁠`

    name =

      `⁠log precision⁠`

    short.name =

      `⁠prec⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 5e-05⁠`

    initial =

      `⁠4⁠`

    fixed =

      `⁠FALSE⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

Model 'besag2'.
  Properties:
    doc =

      `⁠The shared Besag model⁠`

    constr =

      `⁠TRUE⁠`

    nrow.ncol =

      `⁠FALSE⁠`

    augmented =

      `⁠FALSE⁠`

    aug.factor =

      `⁠1⁠`

    aug.constr =

      `⁠1 2⁠`

    n.div.by =

      `⁠2⁠`

    n.required =

      `⁠TRUE⁠`

    set.default.values =

      `⁠TRUE⁠`

    pdf =

      `⁠besag2⁠`

  Number of hyperparmeters is 2.

  Hyperparameter 'theta1'
    hyperid =

      `⁠9001⁠`

    name =

      `⁠log precision⁠`

    short.name =

      `⁠prec⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 5e-05⁠`

    initial =

      `⁠4⁠`

    fixed =

      `⁠FALSE⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠9002⁠`

    name =

      `⁠scaling parameter⁠`

    short.name =

      `⁠a⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠10 10⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

Model 'bym'.
  Properties:
    doc =

      `⁠The BYM-model (Besag-York-Mollier model)⁠`

    constr =

      `⁠TRUE⁠`

    nrow.ncol =

      `⁠FALSE⁠`

    augmented =

      `⁠TRUE⁠`

    aug.factor =

      `⁠2⁠`

    aug.constr =

      `⁠2⁠`

    n.div.by =

      `⁠NULL⁠`

    n.required =

      `⁠TRUE⁠`

    set.default.values =

      `⁠TRUE⁠`

    pdf =

      `⁠bym⁠`

  Number of hyperparmeters is 2.

  Hyperparameter 'theta1'
    hyperid =

      `⁠10001⁠`

    name =

      `⁠log unstructured precision⁠`

    short.name =

      `⁠prec.unstruct⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 5e-04⁠`

    initial =

      `⁠4⁠`

    fixed =

      `⁠FALSE⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠10002⁠`

    name =

      `⁠log spatial precision⁠`

    short.name =

      `⁠prec.spatial⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 5e-04⁠`

    initial =

      `⁠4⁠`

    fixed =

      `⁠FALSE⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

Model 'bym2'.
  Properties:
    doc =

      `⁠The BYM-model with the PC priors⁠`

    constr =

      `⁠TRUE⁠`

    nrow.ncol =

      `⁠FALSE⁠`

    augmented =

      `⁠TRUE⁠`

    aug.factor =

      `⁠2⁠`

    aug.constr =

      `⁠2⁠`

    n.div.by =

      `⁠NULL⁠`

    n.required =

      `⁠TRUE⁠`

    set.default.values =

      `⁠TRUE⁠`

    pdf =

      `⁠bym2⁠`

  Number of hyperparmeters is 2.

  Hyperparameter 'theta1'
    hyperid =

      `⁠11001⁠`

    name =

      `⁠log precision⁠`

    short.name =

      `⁠prec⁠`

    prior =

      `⁠pc.prec⁠`

    param =

      `⁠1 0.01⁠`

    initial =

      `⁠4⁠`

    fixed =

      `⁠FALSE⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠11002⁠`

    name =

      `⁠logit phi⁠`

    short.name =

      `⁠phi⁠`

    prior =

      `⁠pc⁠`

    param =

      `⁠0.5 0.5⁠`

    initial =

      `⁠-3⁠`

    fixed =

      `⁠FALSE⁠`

    to.theta =

      `⁠function(x) log(x / (1 - x))⁠`

    from.theta =

      `⁠function(x) exp(x) / (1 + exp(x))⁠`

Model 'besagproper'.
  Properties:
    doc =

      `⁠A proper version of the Besag model⁠`

    constr =

      `⁠FALSE⁠`

    nrow.ncol =

      `⁠FALSE⁠`

    augmented =

      `⁠FALSE⁠`

    aug.factor =

      `⁠1⁠`

    aug.constr =

      `⁠NULL⁠`

    n.div.by =

      `⁠NULL⁠`

    n.required =

      `⁠TRUE⁠`

    set.default.values =

      `⁠TRUE⁠`

    pdf =

      `⁠besagproper⁠`

  Number of hyperparmeters is 2.

  Hyperparameter 'theta1'
    hyperid =

      `⁠12001⁠`

    name =

      `⁠log precision⁠`

    short.name =

      `⁠prec⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 5e-04⁠`

    initial =

      `⁠2⁠`

    fixed =

      `⁠FALSE⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠12002⁠`

    name =

      `⁠log diagonal⁠`

    short.name =

      `⁠diag⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 1⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

Model 'besagproper2'.
  Properties:
    doc =

      `⁠An alternative proper version of the Besag model⁠`

    constr =

      `⁠FALSE⁠`

    nrow.ncol =

      `⁠FALSE⁠`

    augmented =

      `⁠FALSE⁠`

    aug.factor =

      `⁠1⁠`

    aug.constr =

      `⁠NULL⁠`

    n.div.by =

      `⁠NULL⁠`

    n.required =

      `⁠TRUE⁠`

    set.default.values =

      `⁠TRUE⁠`

    pdf =

      `⁠besagproper2⁠`

  Number of hyperparmeters is 2.

  Hyperparameter 'theta1'
    hyperid =

      `⁠13001⁠`

    name =

      `⁠log precision⁠`

    short.name =

      `⁠prec⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 5e-04⁠`

    initial =

      `⁠2⁠`

    fixed =

      `⁠FALSE⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠13002⁠`

    name =

      `⁠logit lambda⁠`

    short.name =

      `⁠lambda⁠`

    prior =

      `⁠gaussian⁠`

    param =

      `⁠0 0.45⁠`

    initial =

      `⁠3⁠`

    fixed =

      `⁠FALSE⁠`

    to.theta =

      `⁠function(x) log(x / (1 - x))⁠`

    from.theta =

      `⁠function(x) exp(x) / (1 + exp(x))⁠`

Model 'fgn'.
  Properties:
    doc =

      `⁠Fractional Gaussian noise model⁠`

    constr =

      `⁠FALSE⁠`

    nrow.ncol =

      `⁠FALSE⁠`

    augmented =

      `⁠TRUE⁠`

    aug.factor =

      `⁠5⁠`

    aug.constr =

      `⁠1⁠`

    n.div.by =

      `⁠NULL⁠`

    n.required =

      `⁠FALSE⁠`

    set.default.values =

      `⁠TRUE⁠`

    order.default =

      `⁠4⁠`

    order.defined =

      `⁠3 4⁠`

    pdf =

      `⁠fgn⁠`

  Number of hyperparmeters is 2.

  Hyperparameter 'theta1'
    hyperid =

      `⁠13101⁠`

    name =

      `⁠log precision⁠`

    short.name =

      `⁠prec⁠`

    prior =

      `⁠pc.prec⁠`

    param =

      `⁠3 0.01⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠13102⁠`

    name =

      `⁠logit H⁠`

    short.name =

      `⁠H⁠`

    prior =

      `⁠pcfgnh⁠`

    param =

      `⁠0.9 0.1⁠`

    initial =

      `⁠2⁠`

    fixed =

      `⁠FALSE⁠`

    to.theta =

      `⁠function(x) log((2 * x - 1) / (2 * (1 - x)))⁠`

    from.theta =

      `⁠function(x) 0.5 + 0.5 * exp(x) / (1 + exp(x))⁠`

Model 'fgn2'.
  Properties:
    doc =

      `⁠Fractional Gaussian noise model (alt 2)⁠`

    constr =

      `⁠FALSE⁠`

    nrow.ncol =

      `⁠FALSE⁠`

    augmented =

      `⁠TRUE⁠`

    aug.factor =

      `⁠4⁠`

    aug.constr =

      `⁠1⁠`

    n.div.by =

      `⁠NULL⁠`

    n.required =

      `⁠FALSE⁠`

    set.default.values =

      `⁠TRUE⁠`

    order.default =

      `⁠4⁠`

    order.defined =

      `⁠3 4⁠`

    pdf =

      `⁠fgn⁠`

  Number of hyperparmeters is 2.

  Hyperparameter 'theta1'
    hyperid =

      `⁠13111⁠`

    name =

      `⁠log precision⁠`

    short.name =

      `⁠prec⁠`

    prior =

      `⁠pc.prec⁠`

    param =

      `⁠3 0.01⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠13112⁠`

    name =

      `⁠logit H⁠`

    short.name =

      `⁠H⁠`

    prior =

      `⁠pcfgnh⁠`

    param =

      `⁠0.9 0.1⁠`

    initial =

      `⁠2⁠`

    fixed =

      `⁠FALSE⁠`

    to.theta =

      `⁠function(x) log((2 * x - 1) / (2 * (1 - x)))⁠`

    from.theta =

      `⁠function(x) 0.5 + 0.5 * exp(x) / (1 + exp(x))⁠`

Model 'ar1'.
  Properties:
    doc =

      `⁠Auto-regressive model of order 1 (AR(1))⁠`

    constr =

      `⁠FALSE⁠`

    nrow.ncol =

      `⁠FALSE⁠`

    augmented =

      `⁠FALSE⁠`

    aug.factor =

      `⁠1⁠`

    aug.constr =

      `⁠NULL⁠`

    n.div.by =

      `⁠NULL⁠`

    n.required =

      `⁠FALSE⁠`

    set.default.values =

      `⁠FALSE⁠`

    missing.values.warning =

      `⁠TRUE⁠`

    pdf =

      `⁠ar1⁠`

  Number of hyperparmeters is 3.

  Hyperparameter 'theta1'
    hyperid =

      `⁠14001⁠`

    name =

      `⁠log precision⁠`

    short.name =

      `⁠prec⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 5e-05⁠`

    initial =

      `⁠4⁠`

    fixed =

      `⁠FALSE⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠14002⁠`

    name =

      `⁠logit lag one correlation⁠`

    short.name =

      `⁠rho⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 0.15⁠`

    initial =

      `⁠2⁠`

    fixed =

      `⁠FALSE⁠`

    to.theta =

      `⁠function(x) log((1 + x) / (1 - x))⁠`

    from.theta =

      `⁠function(x) 2 * exp(x) / (1 + exp(x)) - 1⁠`

  Hyperparameter 'theta3'
    hyperid =

      `⁠14003⁠`

    name =

      `⁠mean⁠`

    short.name =

      `⁠mean⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 1⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠TRUE⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

Model 'ar1c'.
  Properties:
    doc =

      `⁠Auto-regressive model of order 1 w/covariates⁠`

    constr =

      `⁠FALSE⁠`

    nrow.ncol =

      `⁠FALSE⁠`

    augmented =

      `⁠FALSE⁠`

    aug.factor =

      `⁠1⁠`

    aug.constr =

      `⁠NULL⁠`

    n.div.by =

      `⁠NULL⁠`

    n.required =

      `⁠FALSE⁠`

    set.default.values =

      `⁠TRUE⁠`

    pdf =

      `⁠ar1c⁠`

  Number of hyperparmeters is 2.

  Hyperparameter 'theta1'
    hyperid =

      `⁠14101⁠`

    name =

      `⁠log precision⁠`

    short.name =

      `⁠prec⁠`

    prior =

      `⁠pc.prec⁠`

    param =

      `⁠1 0.01⁠`

    initial =

      `⁠4⁠`

    fixed =

      `⁠FALSE⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠14102⁠`

    name =

      `⁠logit lag one correlation⁠`

    short.name =

      `⁠rho⁠`

    prior =

      `⁠pc.cor0⁠`

    param =

      `⁠0.5 0.5⁠`

    initial =

      `⁠2⁠`

    fixed =

      `⁠FALSE⁠`

    to.theta =

      `⁠function(x) log((1 + x) / (1 - x))⁠`

    from.theta =

      `⁠function(x) 2 * exp(x) / (1 + exp(x)) - 1⁠`

Model 'ar'.
  Properties:
    doc =

      `⁠Auto-regressive model of order p (AR(p))⁠`

    constr =

      `⁠FALSE⁠`

    nrow.ncol =

      `⁠FALSE⁠`

    augmented =

      `⁠FALSE⁠`

    aug.factor =

      `⁠1⁠`

    aug.constr =

      `⁠NULL⁠`

    n.div.by =

      `⁠NULL⁠`

    n.required =

      `⁠FALSE⁠`

    set.default.values =

      `⁠FALSE⁠`

    missing.values.warning =

      `⁠TRUE⁠`

    pdf =

      `⁠ar⁠`

  Number of hyperparmeters is 11.

  Hyperparameter 'theta1'
    hyperid =

      `⁠15001⁠`

    name =

      `⁠log precision⁠`

    short.name =

      `⁠prec⁠`

    initial =

      `⁠4⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠pc.prec⁠`

    param =

      `⁠3 0.01⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠15002⁠`

    name =

      `⁠pacf1⁠`

    short.name =

      `⁠pacf1⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠pc.cor0⁠`

    param =

      `⁠0.5 0.5⁠`

    to.theta =

      `⁠function(x) log((1 + x) / (1 - x))⁠`

    from.theta =

      `⁠function(x) 2 * exp(x) / (1 + exp(x)) - 1⁠`

  Hyperparameter 'theta3'
    hyperid =

      `⁠15003⁠`

    name =

      `⁠pacf2⁠`

    short.name =

      `⁠pacf2⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠pc.cor0⁠`

    param =

      `⁠0.5 0.4⁠`

    to.theta =

      `⁠function(x) log((1 + x) / (1 - x))⁠`

    from.theta =

      `⁠function(x) 2 * exp(x) / (1 + exp(x)) - 1⁠`

  Hyperparameter 'theta4'
    hyperid =

      `⁠15004⁠`

    name =

      `⁠pacf3⁠`

    short.name =

      `⁠pacf3⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠pc.cor0⁠`

    param =

      `⁠0.5 0.3⁠`

    to.theta =

      `⁠function(x) log((1 + x) / (1 - x))⁠`

    from.theta =

      `⁠function(x) 2 * exp(x) / (1 + exp(x)) - 1⁠`

  Hyperparameter 'theta5'
    hyperid =

      `⁠15005⁠`

    name =

      `⁠pacf4⁠`

    short.name =

      `⁠pacf4⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠pc.cor0⁠`

    param =

      `⁠0.5 0.2⁠`

    to.theta =

      `⁠function(x) log((1 + x) / (1 - x))⁠`

    from.theta =

      `⁠function(x) 2 * exp(x) / (1 + exp(x)) - 1⁠`

  Hyperparameter 'theta6'
    hyperid =

      `⁠15006⁠`

    name =

      `⁠pacf5⁠`

    short.name =

      `⁠pacf5⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠pc.cor0⁠`

    param =

      `⁠0.5 0.1⁠`

    to.theta =

      `⁠function(x) log((1 + x) / (1 - x))⁠`

    from.theta =

      `⁠function(x) 2 * exp(x) / (1 + exp(x)) - 1⁠`

  Hyperparameter 'theta7'
    hyperid =

      `⁠15007⁠`

    name =

      `⁠pacf6⁠`

    short.name =

      `⁠pacf6⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠pc.cor0⁠`

    param =

      `⁠0.5 0.1⁠`

    to.theta =

      `⁠function(x) log((1 + x) / (1 - x))⁠`

    from.theta =

      `⁠function(x) 2 * exp(x) / (1 + exp(x)) - 1⁠`

  Hyperparameter 'theta8'
    hyperid =

      `⁠15008⁠`

    name =

      `⁠pacf7⁠`

    short.name =

      `⁠pacf7⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠pc.cor0⁠`

    param =

      `⁠0.5 0.1⁠`

    to.theta =

      `⁠function(x) log((1 + x) / (1 - x))⁠`

    from.theta =

      `⁠function(x) 2 * exp(x) / (1 + exp(x)) - 1⁠`

  Hyperparameter 'theta9'
    hyperid =

      `⁠15009⁠`

    name =

      `⁠pacf8⁠`

    short.name =

      `⁠pacf8⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠pc.cor0⁠`

    param =

      `⁠0.5 0.1⁠`

    to.theta =

      `⁠function(x) log((1 + x) / (1 - x))⁠`

    from.theta =

      `⁠function(x) 2 * exp(x) / (1 + exp(x)) - 1⁠`

  Hyperparameter 'theta10'
    hyperid =

      `⁠15010⁠`

    name =

      `⁠pacf9⁠`

    short.name =

      `⁠pacf9⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠pc.cor0⁠`

    param =

      `⁠0.5 0.1⁠`

    to.theta =

      `⁠function(x) log((1 + x) / (1 - x))⁠`

    from.theta =

      `⁠function(x) 2 * exp(x) / (1 + exp(x)) - 1⁠`

  Hyperparameter 'theta11'
    hyperid =

      `⁠15011⁠`

    name =

      `⁠pacf10⁠`

    short.name =

      `⁠pacf10⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠pc.cor0⁠`

    param =

      `⁠0.5 0.1⁠`

    to.theta =

      `⁠function(x) log((1 + x) / (1 - x))⁠`

    from.theta =

      `⁠function(x) 2 * exp(x) / (1 + exp(x)) - 1⁠`

Model 'ou'.
  Properties:
    doc =

      `⁠The Ornstein-Uhlenbeck process⁠`

    constr =

      `⁠FALSE⁠`

    nrow.ncol =

      `⁠FALSE⁠`

    augmented =

      `⁠FALSE⁠`

    aug.factor =

      `⁠1⁠`

    aug.constr =

      `⁠NULL⁠`

    n.div.by =

      `⁠NULL⁠`

    n.required =

      `⁠FALSE⁠`

    set.default.values =

      `⁠FALSE⁠`

    pdf =

      `⁠ou⁠`

  Number of hyperparmeters is 2.

  Hyperparameter 'theta1'
    hyperid =

      `⁠16001⁠`

    name =

      `⁠log precision⁠`

    short.name =

      `⁠prec⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 5e-05⁠`

    initial =

      `⁠4⁠`

    fixed =

      `⁠FALSE⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠16002⁠`

    name =

      `⁠log phi⁠`

    short.name =

      `⁠phi⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 0.2⁠`

    initial =

      `⁠-1⁠`

    fixed =

      `⁠FALSE⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

Model 'intslope'.
  Properties:
    doc =

      `⁠Intecept-slope model with Wishart-prior⁠`

    constr =

      `⁠FALSE⁠`

    nrow.ncol =

      `⁠FALSE⁠`

    augmented =

      `⁠FALSE⁠`

    aug.factor =

      `⁠1⁠`

    aug.constr =

      `⁠NULL⁠`

    n.div.by =

      `⁠NULL⁠`

    n.required =

      `⁠FALSE⁠`

    set.default.values =

      `⁠TRUE⁠`

    pdf =

      `⁠intslope⁠`

  Number of hyperparmeters is 53.

  Hyperparameter 'theta1'
    hyperid =

      `⁠16101⁠`

    name =

      `⁠log precision1⁠`

    short.name =

      `⁠prec1⁠`

    initial =

      `⁠4⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠wishart2d⁠`

    param =

      `⁠4 1 1 0⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠16102⁠`

    name =

      `⁠log precision2⁠`

    short.name =

      `⁠prec2⁠`

    initial =

      `⁠4⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta3'
    hyperid =

      `⁠16103⁠`

    name =

      `⁠logit correlation⁠`

    short.name =

      `⁠cor⁠`

    initial =

      `⁠4⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) log((1 + x) / (1 - x))⁠`

    from.theta =

      `⁠function(x) 2 * exp(x) / (1 + exp(x)) - 1⁠`

  Hyperparameter 'theta4'
    hyperid =

      `⁠16104⁠`

    name =

      `⁠gamma1⁠`

    short.name =

      `⁠g1⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠TRUE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 36⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta5'
    hyperid =

      `⁠16105⁠`

    name =

      `⁠gamma2⁠`

    short.name =

      `⁠g2⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠TRUE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 36⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta6'
    hyperid =

      `⁠16106⁠`

    name =

      `⁠gamma3⁠`

    short.name =

      `⁠g3⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠TRUE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 36⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta7'
    hyperid =

      `⁠16107⁠`

    name =

      `⁠gamma4⁠`

    short.name =

      `⁠g4⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠TRUE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 36⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta8'
    hyperid =

      `⁠16108⁠`

    name =

      `⁠gamma5⁠`

    short.name =

      `⁠g5⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠TRUE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 36⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta9'
    hyperid =

      `⁠16109⁠`

    name =

      `⁠gamma6⁠`

    short.name =

      `⁠g6⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠TRUE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 36⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta10'
    hyperid =

      `⁠16110⁠`

    name =

      `⁠gamma7⁠`

    short.name =

      `⁠g7⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠TRUE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 36⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta11'
    hyperid =

      `⁠16111⁠`

    name =

      `⁠gamma8⁠`

    short.name =

      `⁠g8⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠TRUE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 36⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta12'
    hyperid =

      `⁠16112⁠`

    name =

      `⁠gamma9⁠`

    short.name =

      `⁠g9⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠TRUE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 36⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta13'
    hyperid =

      `⁠16113⁠`

    name =

      `⁠gamma10⁠`

    short.name =

      `⁠g10⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠TRUE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 36⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta14'
    hyperid =

      `⁠16114⁠`

    name =

      `⁠gamma11⁠`

    short.name =

      `⁠g11⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠TRUE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 36⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta15'
    hyperid =

      `⁠16115⁠`

    name =

      `⁠gamma12⁠`

    short.name =

      `⁠g12⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠TRUE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 36⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta16'
    hyperid =

      `⁠16116⁠`

    name =

      `⁠gamma13⁠`

    short.name =

      `⁠g13⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠TRUE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 36⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta17'
    hyperid =

      `⁠16117⁠`

    name =

      `⁠gamma14⁠`

    short.name =

      `⁠g14⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠TRUE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 36⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta18'
    hyperid =

      `⁠16118⁠`

    name =

      `⁠gamma15⁠`

    short.name =

      `⁠g15⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠TRUE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 36⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta19'
    hyperid =

      `⁠16119⁠`

    name =

      `⁠gamma16⁠`

    short.name =

      `⁠g16⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠TRUE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 36⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta20'
    hyperid =

      `⁠16120⁠`

    name =

      `⁠gamma17⁠`

    short.name =

      `⁠g17⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠TRUE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 36⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta21'
    hyperid =

      `⁠16121⁠`

    name =

      `⁠gamma18⁠`

    short.name =

      `⁠g18⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠TRUE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 36⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta22'
    hyperid =

      `⁠16122⁠`

    name =

      `⁠gamma19⁠`

    short.name =

      `⁠g19⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠TRUE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 36⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta23'
    hyperid =

      `⁠16123⁠`

    name =

      `⁠gamma20⁠`

    short.name =

      `⁠g20⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠TRUE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 36⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta24'
    hyperid =

      `⁠16124⁠`

    name =

      `⁠gamma21⁠`

    short.name =

      `⁠g21⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠TRUE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 36⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta25'
    hyperid =

      `⁠16125⁠`

    name =

      `⁠gamma22⁠`

    short.name =

      `⁠g22⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠TRUE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 36⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta26'
    hyperid =

      `⁠16126⁠`

    name =

      `⁠gamma23⁠`

    short.name =

      `⁠g23⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠TRUE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 36⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta27'
    hyperid =

      `⁠16127⁠`

    name =

      `⁠gamma24⁠`

    short.name =

      `⁠g24⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠TRUE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 36⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta28'
    hyperid =

      `⁠16128⁠`

    name =

      `⁠gamma25⁠`

    short.name =

      `⁠g25⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠TRUE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 36⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta29'
    hyperid =

      `⁠16129⁠`

    name =

      `⁠gamma26⁠`

    short.name =

      `⁠g26⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠TRUE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 36⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta30'
    hyperid =

      `⁠16130⁠`

    name =

      `⁠gamma27⁠`

    short.name =

      `⁠g27⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠TRUE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 36⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta31'
    hyperid =

      `⁠16131⁠`

    name =

      `⁠gamma28⁠`

    short.name =

      `⁠g28⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠TRUE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 36⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta32'
    hyperid =

      `⁠16132⁠`

    name =

      `⁠gamma29⁠`

    short.name =

      `⁠g29⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠TRUE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 36⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta33'
    hyperid =

      `⁠16133⁠`

    name =

      `⁠gamma30⁠`

    short.name =

      `⁠g30⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠TRUE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 36⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta34'
    hyperid =

      `⁠16134⁠`

    name =

      `⁠gamma31⁠`

    short.name =

      `⁠g31⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠TRUE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 36⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta35'
    hyperid =

      `⁠16135⁠`

    name =

      `⁠gamma32⁠`

    short.name =

      `⁠g32⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠TRUE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 36⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta36'
    hyperid =

      `⁠16136⁠`

    name =

      `⁠gamma33⁠`

    short.name =

      `⁠g33⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠TRUE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 36⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta37'
    hyperid =

      `⁠16137⁠`

    name =

      `⁠gamma34⁠`

    short.name =

      `⁠g34⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠TRUE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 36⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta38'
    hyperid =

      `⁠16138⁠`

    name =

      `⁠gamma35⁠`

    short.name =

      `⁠g35⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠TRUE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 36⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta39'
    hyperid =

      `⁠16139⁠`

    name =

      `⁠gamma36⁠`

    short.name =

      `⁠g36⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠TRUE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 36⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta40'
    hyperid =

      `⁠16140⁠`

    name =

      `⁠gamma37⁠`

    short.name =

      `⁠g37⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠TRUE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 36⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta41'
    hyperid =

      `⁠16141⁠`

    name =

      `⁠gamma38⁠`

    short.name =

      `⁠g38⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠TRUE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 36⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta42'
    hyperid =

      `⁠16142⁠`

    name =

      `⁠gamma39⁠`

    short.name =

      `⁠g39⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠TRUE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 36⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta43'
    hyperid =

      `⁠16143⁠`

    name =

      `⁠gamma40⁠`

    short.name =

      `⁠g40⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠TRUE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 36⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta44'
    hyperid =

      `⁠16144⁠`

    name =

      `⁠gamma41⁠`

    short.name =

      `⁠g41⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠TRUE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 36⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta45'
    hyperid =

      `⁠16145⁠`

    name =

      `⁠gamma42⁠`

    short.name =

      `⁠g42⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠TRUE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 36⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta46'
    hyperid =

      `⁠16146⁠`

    name =

      `⁠gamma43⁠`

    short.name =

      `⁠g43⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠TRUE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 36⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta47'
    hyperid =

      `⁠16147⁠`

    name =

      `⁠gamma44⁠`

    short.name =

      `⁠g44⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠TRUE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 36⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta48'
    hyperid =

      `⁠16148⁠`

    name =

      `⁠gamma45⁠`

    short.name =

      `⁠g45⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠TRUE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 36⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta49'
    hyperid =

      `⁠16149⁠`

    name =

      `⁠gamma46⁠`

    short.name =

      `⁠g46⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠TRUE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 36⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta50'
    hyperid =

      `⁠16150⁠`

    name =

      `⁠gamma47⁠`

    short.name =

      `⁠g47⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠TRUE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 36⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta51'
    hyperid =

      `⁠16151⁠`

    name =

      `⁠gamma48⁠`

    short.name =

      `⁠g48⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠TRUE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 36⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta52'
    hyperid =

      `⁠16152⁠`

    name =

      `⁠gamma49⁠`

    short.name =

      `⁠g49⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠TRUE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 36⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta53'
    hyperid =

      `⁠16153⁠`

    name =

      `⁠gamma50⁠`

    short.name =

      `⁠g50⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠TRUE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 36⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

Model 'generic'.
  Properties:
    doc =

      `⁠A generic model⁠`

    constr =

      `⁠FALSE⁠`

    nrow.ncol =

      `⁠FALSE⁠`

    augmented =

      `⁠FALSE⁠`

    aug.factor =

      `⁠1⁠`

    aug.constr =

      `⁠NULL⁠`

    n.div.by =

      `⁠NULL⁠`

    n.required =

      `⁠TRUE⁠`

    set.default.values =

      `⁠TRUE⁠`

    pdf =

      `⁠generic0⁠`

  Number of hyperparmeters is 1.

  Hyperparameter 'theta'
    hyperid =

      `⁠17001⁠`

    name =

      `⁠log precision⁠`

    short.name =

      `⁠prec⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 5e-05⁠`

    initial =

      `⁠4⁠`

    fixed =

      `⁠FALSE⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

Model 'generic0'.
  Properties:
    doc =

      `⁠A generic model (type 0)⁠`

    constr =

      `⁠FALSE⁠`

    nrow.ncol =

      `⁠FALSE⁠`

    augmented =

      `⁠FALSE⁠`

    aug.factor =

      `⁠1⁠`

    aug.constr =

      `⁠NULL⁠`

    n.div.by =

      `⁠NULL⁠`

    n.required =

      `⁠TRUE⁠`

    set.default.values =

      `⁠TRUE⁠`

    pdf =

      `⁠generic0⁠`

  Number of hyperparmeters is 1.

  Hyperparameter 'theta'
    hyperid =

      `⁠18001⁠`

    name =

      `⁠log precision⁠`

    short.name =

      `⁠prec⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 5e-05⁠`

    initial =

      `⁠4⁠`

    fixed =

      `⁠FALSE⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

Model 'generic1'.
  Properties:
    doc =

      `⁠A generic model (type 1)⁠`

    constr =

      `⁠FALSE⁠`

    nrow.ncol =

      `⁠FALSE⁠`

    augmented =

      `⁠FALSE⁠`

    aug.factor =

      `⁠1⁠`

    aug.constr =

      `⁠NULL⁠`

    n.div.by =

      `⁠NULL⁠`

    n.required =

      `⁠TRUE⁠`

    set.default.values =

      `⁠TRUE⁠`

    pdf =

      `⁠generic1⁠`

  Number of hyperparmeters is 2.

  Hyperparameter 'theta1'
    hyperid =

      `⁠19001⁠`

    name =

      `⁠log precision⁠`

    short.name =

      `⁠prec⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 5e-05⁠`

    initial =

      `⁠4⁠`

    fixed =

      `⁠FALSE⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠19002⁠`

    name =

      `⁠beta⁠`

    short.name =

      `⁠beta⁠`

    initial =

      `⁠2⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠gaussian⁠`

    param =

      `⁠0 0.1⁠`

    to.theta =

      `⁠function(x) log(x / (1 - x))⁠`

    from.theta =

      `⁠function(x) exp(x) / (1 + exp(x))⁠`

Model 'generic2'.
  Properties:
    doc =

      `⁠A generic model (type 2)⁠`

    constr =

      `⁠FALSE⁠`

    nrow.ncol =

      `⁠FALSE⁠`

    augmented =

      `⁠FALSE⁠`

    aug.factor =

      `⁠2⁠`

    aug.constr =

      `⁠2⁠`

    n.div.by =

      `⁠NULL⁠`

    n.required =

      `⁠TRUE⁠`

    set.default.values =

      `⁠TRUE⁠`

    pdf =

      `⁠generic2⁠`

  Number of hyperparmeters is 2.

  Hyperparameter 'theta1'
    hyperid =

      `⁠20001⁠`

    name =

      `⁠log precision cmatrix⁠`

    short.name =

      `⁠prec⁠`

    initial =

      `⁠4⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 5e-05⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠20002⁠`

    name =

      `⁠log precision random⁠`

    short.name =

      `⁠prec.random⁠`

    initial =

      `⁠4⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 0.001⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

Model 'generic3'.
  Properties:
    doc =

      `⁠A generic model (type 3)⁠`

    constr =

      `⁠FALSE⁠`

    nrow.ncol =

      `⁠FALSE⁠`

    augmented =

      `⁠FALSE⁠`

    aug.factor =

      `⁠1⁠`

    aug.constr =

      `⁠NULL⁠`

    n.div.by =

      `⁠NULL⁠`

    n.required =

      `⁠TRUE⁠`

    set.default.values =

      `⁠TRUE⁠`

    pdf =

      `⁠generic3⁠`

  Number of hyperparmeters is 11.

  Hyperparameter 'theta1'
    hyperid =

      `⁠21001⁠`

    name =

      `⁠log precision1⁠`

    short.name =

      `⁠prec1⁠`

    initial =

      `⁠4⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 5e-05⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠21002⁠`

    name =

      `⁠log precision2⁠`

    short.name =

      `⁠prec2⁠`

    initial =

      `⁠4⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 5e-05⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta3'
    hyperid =

      `⁠21003⁠`

    name =

      `⁠log precision3⁠`

    short.name =

      `⁠prec3⁠`

    initial =

      `⁠4⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 5e-05⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta4'
    hyperid =

      `⁠21004⁠`

    name =

      `⁠log precision4⁠`

    short.name =

      `⁠prec4⁠`

    initial =

      `⁠4⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 5e-05⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta5'
    hyperid =

      `⁠21005⁠`

    name =

      `⁠log precision5⁠`

    short.name =

      `⁠prec5⁠`

    initial =

      `⁠4⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 5e-05⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta6'
    hyperid =

      `⁠21006⁠`

    name =

      `⁠log precision6⁠`

    short.name =

      `⁠prec6⁠`

    initial =

      `⁠4⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 5e-05⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta7'
    hyperid =

      `⁠21007⁠`

    name =

      `⁠log precision7⁠`

    short.name =

      `⁠prec7⁠`

    initial =

      `⁠4⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 5e-05⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta8'
    hyperid =

      `⁠21008⁠`

    name =

      `⁠log precision8⁠`

    short.name =

      `⁠prec8⁠`

    initial =

      `⁠4⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 5e-05⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta9'
    hyperid =

      `⁠21009⁠`

    name =

      `⁠log precision9⁠`

    short.name =

      `⁠prec9⁠`

    initial =

      `⁠4⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 5e-05⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta10'
    hyperid =

      `⁠21010⁠`

    name =

      `⁠log precision10⁠`

    short.name =

      `⁠prec10⁠`

    initial =

      `⁠4⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 5e-05⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta11'
    hyperid =

      `⁠21011⁠`

    name =

      `⁠log precision common⁠`

    short.name =

      `⁠prec.common⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠TRUE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 5e-05⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

Model 'spde'.
  Properties:
    doc =

      `⁠A SPDE model⁠`

    constr =

      `⁠FALSE⁠`

    nrow.ncol =

      `⁠FALSE⁠`

    augmented =

      `⁠FALSE⁠`

    aug.factor =

      `⁠1⁠`

    aug.constr =

      `⁠NULL⁠`

    n.div.by =

      `⁠NULL⁠`

    n.required =

      `⁠TRUE⁠`

    set.default.values =

      `⁠TRUE⁠`

    pdf =

      `⁠spde⁠`

  Number of hyperparmeters is 4.

  Hyperparameter 'theta1'
    hyperid =

      `⁠22001⁠`

    name =

      `⁠theta.T⁠`

    short.name =

      `⁠T⁠`

    initial =

      `⁠2⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 1⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠22002⁠`

    name =

      `⁠theta.K⁠`

    short.name =

      `⁠K⁠`

    initial =

      `⁠-2⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 1⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta3'
    hyperid =

      `⁠22003⁠`

    name =

      `⁠theta.KT⁠`

    short.name =

      `⁠KT⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 1⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta4'
    hyperid =

      `⁠22004⁠`

    name =

      `⁠theta.OC⁠`

    short.name =

      `⁠OC⁠`

    initial =

      `⁠-20⁠`

    fixed =

      `⁠TRUE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 0.2⁠`

    to.theta =

      `⁠function(x) log(x / (1 - x))⁠`

    from.theta =

      `⁠function(x) exp(x) / (1 + exp(x))⁠`

Model 'spde2'.
  Properties:
    doc =

      `⁠A SPDE2 model⁠`

    constr =

      `⁠FALSE⁠`

    nrow.ncol =

      `⁠FALSE⁠`

    augmented =

      `⁠FALSE⁠`

    aug.factor =

      `⁠1⁠`

    aug.constr =

      `⁠NULL⁠`

    n.div.by =

      `⁠NULL⁠`

    n.required =

      `⁠TRUE⁠`

    set.default.values =

      `⁠TRUE⁠`

    pdf =

      `⁠spde2⁠`

  Number of hyperparmeters is 100.

  Hyperparameter 'theta1'
    hyperid =

      `⁠23001⁠`

    name =

      `⁠theta1⁠`

    short.name =

      `⁠t1⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠mvnorm⁠`

    param =

      `⁠1 1⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠23002⁠`

    name =

      `⁠theta2⁠`

    short.name =

      `⁠t2⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta3'
    hyperid =

      `⁠23003⁠`

    name =

      `⁠theta3⁠`

    short.name =

      `⁠t3⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta4'
    hyperid =

      `⁠23004⁠`

    name =

      `⁠theta4⁠`

    short.name =

      `⁠t4⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta5'
    hyperid =

      `⁠23005⁠`

    name =

      `⁠theta5⁠`

    short.name =

      `⁠t5⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta6'
    hyperid =

      `⁠23006⁠`

    name =

      `⁠theta6⁠`

    short.name =

      `⁠t6⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta7'
    hyperid =

      `⁠23007⁠`

    name =

      `⁠theta7⁠`

    short.name =

      `⁠t7⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta8'
    hyperid =

      `⁠23008⁠`

    name =

      `⁠theta8⁠`

    short.name =

      `⁠t8⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta9'
    hyperid =

      `⁠23009⁠`

    name =

      `⁠theta9⁠`

    short.name =

      `⁠t9⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta10'
    hyperid =

      `⁠23010⁠`

    name =

      `⁠theta10⁠`

    short.name =

      `⁠t10⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta11'
    hyperid =

      `⁠23011⁠`

    name =

      `⁠theta11⁠`

    short.name =

      `⁠t11⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta12'
    hyperid =

      `⁠23012⁠`

    name =

      `⁠theta12⁠`

    short.name =

      `⁠t12⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta13'
    hyperid =

      `⁠23013⁠`

    name =

      `⁠theta13⁠`

    short.name =

      `⁠t13⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta14'
    hyperid =

      `⁠23014⁠`

    name =

      `⁠theta14⁠`

    short.name =

      `⁠t14⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta15'
    hyperid =

      `⁠23015⁠`

    name =

      `⁠theta15⁠`

    short.name =

      `⁠t15⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta16'
    hyperid =

      `⁠23016⁠`

    name =

      `⁠theta16⁠`

    short.name =

      `⁠t16⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta17'
    hyperid =

      `⁠23017⁠`

    name =

      `⁠theta17⁠`

    short.name =

      `⁠t17⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta18'
    hyperid =

      `⁠23018⁠`

    name =

      `⁠theta18⁠`

    short.name =

      `⁠t18⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta19'
    hyperid =

      `⁠23019⁠`

    name =

      `⁠theta19⁠`

    short.name =

      `⁠t19⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta20'
    hyperid =

      `⁠23020⁠`

    name =

      `⁠theta20⁠`

    short.name =

      `⁠t20⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta21'
    hyperid =

      `⁠23021⁠`

    name =

      `⁠theta21⁠`

    short.name =

      `⁠t21⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta22'
    hyperid =

      `⁠23022⁠`

    name =

      `⁠theta22⁠`

    short.name =

      `⁠t22⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta23'
    hyperid =

      `⁠23023⁠`

    name =

      `⁠theta23⁠`

    short.name =

      `⁠t23⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta24'
    hyperid =

      `⁠23024⁠`

    name =

      `⁠theta24⁠`

    short.name =

      `⁠t24⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta25'
    hyperid =

      `⁠23025⁠`

    name =

      `⁠theta25⁠`

    short.name =

      `⁠t25⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta26'
    hyperid =

      `⁠23026⁠`

    name =

      `⁠theta26⁠`

    short.name =

      `⁠t26⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta27'
    hyperid =

      `⁠23027⁠`

    name =

      `⁠theta27⁠`

    short.name =

      `⁠t27⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta28'
    hyperid =

      `⁠23028⁠`

    name =

      `⁠theta28⁠`

    short.name =

      `⁠t28⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta29'
    hyperid =

      `⁠23029⁠`

    name =

      `⁠theta29⁠`

    short.name =

      `⁠t29⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta30'
    hyperid =

      `⁠23030⁠`

    name =

      `⁠theta30⁠`

    short.name =

      `⁠t30⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta31'
    hyperid =

      `⁠23031⁠`

    name =

      `⁠theta31⁠`

    short.name =

      `⁠t31⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta32'
    hyperid =

      `⁠23032⁠`

    name =

      `⁠theta32⁠`

    short.name =

      `⁠t32⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta33'
    hyperid =

      `⁠23033⁠`

    name =

      `⁠theta33⁠`

    short.name =

      `⁠t33⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta34'
    hyperid =

      `⁠23034⁠`

    name =

      `⁠theta34⁠`

    short.name =

      `⁠t34⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta35'
    hyperid =

      `⁠23035⁠`

    name =

      `⁠theta35⁠`

    short.name =

      `⁠t35⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta36'
    hyperid =

      `⁠23036⁠`

    name =

      `⁠theta36⁠`

    short.name =

      `⁠t36⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta37'
    hyperid =

      `⁠23037⁠`

    name =

      `⁠theta37⁠`

    short.name =

      `⁠t37⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta38'
    hyperid =

      `⁠23038⁠`

    name =

      `⁠theta38⁠`

    short.name =

      `⁠t38⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta39'
    hyperid =

      `⁠23039⁠`

    name =

      `⁠theta39⁠`

    short.name =

      `⁠t39⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta40'
    hyperid =

      `⁠23040⁠`

    name =

      `⁠theta40⁠`

    short.name =

      `⁠t40⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta41'
    hyperid =

      `⁠23041⁠`

    name =

      `⁠theta41⁠`

    short.name =

      `⁠t41⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta42'
    hyperid =

      `⁠23042⁠`

    name =

      `⁠theta42⁠`

    short.name =

      `⁠t42⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta43'
    hyperid =

      `⁠23043⁠`

    name =

      `⁠theta43⁠`

    short.name =

      `⁠t43⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta44'
    hyperid =

      `⁠23044⁠`

    name =

      `⁠theta44⁠`

    short.name =

      `⁠t44⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta45'
    hyperid =

      `⁠23045⁠`

    name =

      `⁠theta45⁠`

    short.name =

      `⁠t45⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta46'
    hyperid =

      `⁠23046⁠`

    name =

      `⁠theta46⁠`

    short.name =

      `⁠t46⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta47'
    hyperid =

      `⁠23047⁠`

    name =

      `⁠theta47⁠`

    short.name =

      `⁠t47⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta48'
    hyperid =

      `⁠23048⁠`

    name =

      `⁠theta48⁠`

    short.name =

      `⁠t48⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta49'
    hyperid =

      `⁠23049⁠`

    name =

      `⁠theta49⁠`

    short.name =

      `⁠t49⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta50'
    hyperid =

      `⁠23050⁠`

    name =

      `⁠theta50⁠`

    short.name =

      `⁠t50⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta51'
    hyperid =

      `⁠23051⁠`

    name =

      `⁠theta51⁠`

    short.name =

      `⁠t51⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta52'
    hyperid =

      `⁠23052⁠`

    name =

      `⁠theta52⁠`

    short.name =

      `⁠t52⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta53'
    hyperid =

      `⁠23053⁠`

    name =

      `⁠theta53⁠`

    short.name =

      `⁠t53⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta54'
    hyperid =

      `⁠23054⁠`

    name =

      `⁠theta54⁠`

    short.name =

      `⁠t54⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta55'
    hyperid =

      `⁠23055⁠`

    name =

      `⁠theta55⁠`

    short.name =

      `⁠t55⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta56'
    hyperid =

      `⁠23056⁠`

    name =

      `⁠theta56⁠`

    short.name =

      `⁠t56⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta57'
    hyperid =

      `⁠23057⁠`

    name =

      `⁠theta57⁠`

    short.name =

      `⁠t57⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta58'
    hyperid =

      `⁠23058⁠`

    name =

      `⁠theta58⁠`

    short.name =

      `⁠t58⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta59'
    hyperid =

      `⁠23059⁠`

    name =

      `⁠theta59⁠`

    short.name =

      `⁠t59⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta60'
    hyperid =

      `⁠23060⁠`

    name =

      `⁠theta60⁠`

    short.name =

      `⁠t60⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta61'
    hyperid =

      `⁠23061⁠`

    name =

      `⁠theta61⁠`

    short.name =

      `⁠t61⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta62'
    hyperid =

      `⁠23062⁠`

    name =

      `⁠theta62⁠`

    short.name =

      `⁠t62⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta63'
    hyperid =

      `⁠23063⁠`

    name =

      `⁠theta63⁠`

    short.name =

      `⁠t63⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta64'
    hyperid =

      `⁠23064⁠`

    name =

      `⁠theta64⁠`

    short.name =

      `⁠t64⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta65'
    hyperid =

      `⁠23065⁠`

    name =

      `⁠theta65⁠`

    short.name =

      `⁠t65⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta66'
    hyperid =

      `⁠23066⁠`

    name =

      `⁠theta66⁠`

    short.name =

      `⁠t66⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta67'
    hyperid =

      `⁠23067⁠`

    name =

      `⁠theta67⁠`

    short.name =

      `⁠t67⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta68'
    hyperid =

      `⁠23068⁠`

    name =

      `⁠theta68⁠`

    short.name =

      `⁠t68⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta69'
    hyperid =

      `⁠23069⁠`

    name =

      `⁠theta69⁠`

    short.name =

      `⁠t69⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta70'
    hyperid =

      `⁠23070⁠`

    name =

      `⁠theta70⁠`

    short.name =

      `⁠t70⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta71'
    hyperid =

      `⁠23071⁠`

    name =

      `⁠theta71⁠`

    short.name =

      `⁠t71⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta72'
    hyperid =

      `⁠23072⁠`

    name =

      `⁠theta72⁠`

    short.name =

      `⁠t72⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta73'
    hyperid =

      `⁠23073⁠`

    name =

      `⁠theta73⁠`

    short.name =

      `⁠t73⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta74'
    hyperid =

      `⁠23074⁠`

    name =

      `⁠theta74⁠`

    short.name =

      `⁠t74⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta75'
    hyperid =

      `⁠23075⁠`

    name =

      `⁠theta75⁠`

    short.name =

      `⁠t75⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta76'
    hyperid =

      `⁠23076⁠`

    name =

      `⁠theta76⁠`

    short.name =

      `⁠t76⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta77'
    hyperid =

      `⁠23077⁠`

    name =

      `⁠theta77⁠`

    short.name =

      `⁠t77⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta78'
    hyperid =

      `⁠23078⁠`

    name =

      `⁠theta78⁠`

    short.name =

      `⁠t78⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta79'
    hyperid =

      `⁠23079⁠`

    name =

      `⁠theta79⁠`

    short.name =

      `⁠t79⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta80'
    hyperid =

      `⁠23080⁠`

    name =

      `⁠theta80⁠`

    short.name =

      `⁠t80⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta81'
    hyperid =

      `⁠23081⁠`

    name =

      `⁠theta81⁠`

    short.name =

      `⁠t81⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta82'
    hyperid =

      `⁠23082⁠`

    name =

      `⁠theta82⁠`

    short.name =

      `⁠t82⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta83'
    hyperid =

      `⁠23083⁠`

    name =

      `⁠theta83⁠`

    short.name =

      `⁠t83⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta84'
    hyperid =

      `⁠23084⁠`

    name =

      `⁠theta84⁠`

    short.name =

      `⁠t84⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta85'
    hyperid =

      `⁠23085⁠`

    name =

      `⁠theta85⁠`

    short.name =

      `⁠t85⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta86'
    hyperid =

      `⁠23086⁠`

    name =

      `⁠theta86⁠`

    short.name =

      `⁠t86⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta87'
    hyperid =

      `⁠23087⁠`

    name =

      `⁠theta87⁠`

    short.name =

      `⁠t87⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta88'
    hyperid =

      `⁠23088⁠`

    name =

      `⁠theta88⁠`

    short.name =

      `⁠t88⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta89'
    hyperid =

      `⁠23089⁠`

    name =

      `⁠theta89⁠`

    short.name =

      `⁠t89⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta90'
    hyperid =

      `⁠23090⁠`

    name =

      `⁠theta90⁠`

    short.name =

      `⁠t90⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta91'
    hyperid =

      `⁠23091⁠`

    name =

      `⁠theta91⁠`

    short.name =

      `⁠t91⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta92'
    hyperid =

      `⁠23092⁠`

    name =

      `⁠theta92⁠`

    short.name =

      `⁠t92⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta93'
    hyperid =

      `⁠23093⁠`

    name =

      `⁠theta93⁠`

    short.name =

      `⁠t93⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta94'
    hyperid =

      `⁠23094⁠`

    name =

      `⁠theta94⁠`

    short.name =

      `⁠t94⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta95'
    hyperid =

      `⁠23095⁠`

    name =

      `⁠theta95⁠`

    short.name =

      `⁠t95⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta96'
    hyperid =

      `⁠23096⁠`

    name =

      `⁠theta96⁠`

    short.name =

      `⁠t96⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta97'
    hyperid =

      `⁠23097⁠`

    name =

      `⁠theta97⁠`

    short.name =

      `⁠t97⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta98'
    hyperid =

      `⁠23098⁠`

    name =

      `⁠theta98⁠`

    short.name =

      `⁠t98⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta99'
    hyperid =

      `⁠23099⁠`

    name =

      `⁠theta99⁠`

    short.name =

      `⁠t99⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta100'
    hyperid =

      `⁠23100⁠`

    name =

      `⁠theta100⁠`

    short.name =

      `⁠t100⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

Model 'spde3'.
  Properties:
    doc =

      `⁠A SPDE3 model⁠`

    constr =

      `⁠FALSE⁠`

    nrow.ncol =

      `⁠FALSE⁠`

    augmented =

      `⁠FALSE⁠`

    aug.factor =

      `⁠1⁠`

    aug.constr =

      `⁠NULL⁠`

    n.div.by =

      `⁠NULL⁠`

    n.required =

      `⁠TRUE⁠`

    set.default.values =

      `⁠TRUE⁠`

    pdf =

      `⁠spde3⁠`

  Number of hyperparmeters is 100.

  Hyperparameter 'theta1'
    hyperid =

      `⁠24001⁠`

    name =

      `⁠theta1⁠`

    short.name =

      `⁠t1⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠mvnorm⁠`

    param =

      `⁠1 1⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠24002⁠`

    name =

      `⁠theta2⁠`

    short.name =

      `⁠t2⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta3'
    hyperid =

      `⁠24003⁠`

    name =

      `⁠theta3⁠`

    short.name =

      `⁠t3⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta4'
    hyperid =

      `⁠24004⁠`

    name =

      `⁠theta4⁠`

    short.name =

      `⁠t4⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta5'
    hyperid =

      `⁠24005⁠`

    name =

      `⁠theta5⁠`

    short.name =

      `⁠t5⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta6'
    hyperid =

      `⁠24006⁠`

    name =

      `⁠theta6⁠`

    short.name =

      `⁠t6⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta7'
    hyperid =

      `⁠24007⁠`

    name =

      `⁠theta7⁠`

    short.name =

      `⁠t7⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta8'
    hyperid =

      `⁠24008⁠`

    name =

      `⁠theta8⁠`

    short.name =

      `⁠t8⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta9'
    hyperid =

      `⁠24009⁠`

    name =

      `⁠theta9⁠`

    short.name =

      `⁠t9⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta10'
    hyperid =

      `⁠24010⁠`

    name =

      `⁠theta10⁠`

    short.name =

      `⁠t10⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta11'
    hyperid =

      `⁠24011⁠`

    name =

      `⁠theta11⁠`

    short.name =

      `⁠t11⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta12'
    hyperid =

      `⁠24012⁠`

    name =

      `⁠theta12⁠`

    short.name =

      `⁠t12⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta13'
    hyperid =

      `⁠24013⁠`

    name =

      `⁠theta13⁠`

    short.name =

      `⁠t13⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta14'
    hyperid =

      `⁠24014⁠`

    name =

      `⁠theta14⁠`

    short.name =

      `⁠t14⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta15'
    hyperid =

      `⁠24015⁠`

    name =

      `⁠theta15⁠`

    short.name =

      `⁠t15⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta16'
    hyperid =

      `⁠24016⁠`

    name =

      `⁠theta16⁠`

    short.name =

      `⁠t16⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta17'
    hyperid =

      `⁠24017⁠`

    name =

      `⁠theta17⁠`

    short.name =

      `⁠t17⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta18'
    hyperid =

      `⁠24018⁠`

    name =

      `⁠theta18⁠`

    short.name =

      `⁠t18⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta19'
    hyperid =

      `⁠24019⁠`

    name =

      `⁠theta19⁠`

    short.name =

      `⁠t19⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta20'
    hyperid =

      `⁠24020⁠`

    name =

      `⁠theta20⁠`

    short.name =

      `⁠t20⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta21'
    hyperid =

      `⁠24021⁠`

    name =

      `⁠theta21⁠`

    short.name =

      `⁠t21⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta22'
    hyperid =

      `⁠24022⁠`

    name =

      `⁠theta22⁠`

    short.name =

      `⁠t22⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta23'
    hyperid =

      `⁠24023⁠`

    name =

      `⁠theta23⁠`

    short.name =

      `⁠t23⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta24'
    hyperid =

      `⁠24024⁠`

    name =

      `⁠theta24⁠`

    short.name =

      `⁠t24⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta25'
    hyperid =

      `⁠24025⁠`

    name =

      `⁠theta25⁠`

    short.name =

      `⁠t25⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta26'
    hyperid =

      `⁠24026⁠`

    name =

      `⁠theta26⁠`

    short.name =

      `⁠t26⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta27'
    hyperid =

      `⁠24027⁠`

    name =

      `⁠theta27⁠`

    short.name =

      `⁠t27⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta28'
    hyperid =

      `⁠24028⁠`

    name =

      `⁠theta28⁠`

    short.name =

      `⁠t28⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta29'
    hyperid =

      `⁠24029⁠`

    name =

      `⁠theta29⁠`

    short.name =

      `⁠t29⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta30'
    hyperid =

      `⁠24030⁠`

    name =

      `⁠theta30⁠`

    short.name =

      `⁠t30⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta31'
    hyperid =

      `⁠24031⁠`

    name =

      `⁠theta31⁠`

    short.name =

      `⁠t31⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta32'
    hyperid =

      `⁠24032⁠`

    name =

      `⁠theta32⁠`

    short.name =

      `⁠t32⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta33'
    hyperid =

      `⁠24033⁠`

    name =

      `⁠theta33⁠`

    short.name =

      `⁠t33⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta34'
    hyperid =

      `⁠24034⁠`

    name =

      `⁠theta34⁠`

    short.name =

      `⁠t34⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta35'
    hyperid =

      `⁠24035⁠`

    name =

      `⁠theta35⁠`

    short.name =

      `⁠t35⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta36'
    hyperid =

      `⁠24036⁠`

    name =

      `⁠theta36⁠`

    short.name =

      `⁠t36⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta37'
    hyperid =

      `⁠24037⁠`

    name =

      `⁠theta37⁠`

    short.name =

      `⁠t37⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta38'
    hyperid =

      `⁠24038⁠`

    name =

      `⁠theta38⁠`

    short.name =

      `⁠t38⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta39'
    hyperid =

      `⁠24039⁠`

    name =

      `⁠theta39⁠`

    short.name =

      `⁠t39⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta40'
    hyperid =

      `⁠24040⁠`

    name =

      `⁠theta40⁠`

    short.name =

      `⁠t40⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta41'
    hyperid =

      `⁠24041⁠`

    name =

      `⁠theta41⁠`

    short.name =

      `⁠t41⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta42'
    hyperid =

      `⁠24042⁠`

    name =

      `⁠theta42⁠`

    short.name =

      `⁠t42⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta43'
    hyperid =

      `⁠24043⁠`

    name =

      `⁠theta43⁠`

    short.name =

      `⁠t43⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta44'
    hyperid =

      `⁠24044⁠`

    name =

      `⁠theta44⁠`

    short.name =

      `⁠t44⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta45'
    hyperid =

      `⁠24045⁠`

    name =

      `⁠theta45⁠`

    short.name =

      `⁠t45⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta46'
    hyperid =

      `⁠24046⁠`

    name =

      `⁠theta46⁠`

    short.name =

      `⁠t46⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta47'
    hyperid =

      `⁠24047⁠`

    name =

      `⁠theta47⁠`

    short.name =

      `⁠t47⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta48'
    hyperid =

      `⁠24048⁠`

    name =

      `⁠theta48⁠`

    short.name =

      `⁠t48⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta49'
    hyperid =

      `⁠24049⁠`

    name =

      `⁠theta49⁠`

    short.name =

      `⁠t49⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta50'
    hyperid =

      `⁠24050⁠`

    name =

      `⁠theta50⁠`

    short.name =

      `⁠t50⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta51'
    hyperid =

      `⁠24051⁠`

    name =

      `⁠theta51⁠`

    short.name =

      `⁠t51⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta52'
    hyperid =

      `⁠24052⁠`

    name =

      `⁠theta52⁠`

    short.name =

      `⁠t52⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta53'
    hyperid =

      `⁠24053⁠`

    name =

      `⁠theta53⁠`

    short.name =

      `⁠t53⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta54'
    hyperid =

      `⁠24054⁠`

    name =

      `⁠theta54⁠`

    short.name =

      `⁠t54⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta55'
    hyperid =

      `⁠24055⁠`

    name =

      `⁠theta55⁠`

    short.name =

      `⁠t55⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta56'
    hyperid =

      `⁠24056⁠`

    name =

      `⁠theta56⁠`

    short.name =

      `⁠t56⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta57'
    hyperid =

      `⁠24057⁠`

    name =

      `⁠theta57⁠`

    short.name =

      `⁠t57⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta58'
    hyperid =

      `⁠24058⁠`

    name =

      `⁠theta58⁠`

    short.name =

      `⁠t58⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta59'
    hyperid =

      `⁠24059⁠`

    name =

      `⁠theta59⁠`

    short.name =

      `⁠t59⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta60'
    hyperid =

      `⁠24060⁠`

    name =

      `⁠theta60⁠`

    short.name =

      `⁠t60⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta61'
    hyperid =

      `⁠24061⁠`

    name =

      `⁠theta61⁠`

    short.name =

      `⁠t61⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta62'
    hyperid =

      `⁠24062⁠`

    name =

      `⁠theta62⁠`

    short.name =

      `⁠t62⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta63'
    hyperid =

      `⁠24063⁠`

    name =

      `⁠theta63⁠`

    short.name =

      `⁠t63⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta64'
    hyperid =

      `⁠24064⁠`

    name =

      `⁠theta64⁠`

    short.name =

      `⁠t64⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta65'
    hyperid =

      `⁠24065⁠`

    name =

      `⁠theta65⁠`

    short.name =

      `⁠t65⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta66'
    hyperid =

      `⁠24066⁠`

    name =

      `⁠theta66⁠`

    short.name =

      `⁠t66⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta67'
    hyperid =

      `⁠24067⁠`

    name =

      `⁠theta67⁠`

    short.name =

      `⁠t67⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta68'
    hyperid =

      `⁠24068⁠`

    name =

      `⁠theta68⁠`

    short.name =

      `⁠t68⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta69'
    hyperid =

      `⁠24069⁠`

    name =

      `⁠theta69⁠`

    short.name =

      `⁠t69⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta70'
    hyperid =

      `⁠24070⁠`

    name =

      `⁠theta70⁠`

    short.name =

      `⁠t70⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta71'
    hyperid =

      `⁠24071⁠`

    name =

      `⁠theta71⁠`

    short.name =

      `⁠t71⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta72'
    hyperid =

      `⁠24072⁠`

    name =

      `⁠theta72⁠`

    short.name =

      `⁠t72⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta73'
    hyperid =

      `⁠24073⁠`

    name =

      `⁠theta73⁠`

    short.name =

      `⁠t73⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta74'
    hyperid =

      `⁠24074⁠`

    name =

      `⁠theta74⁠`

    short.name =

      `⁠t74⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta75'
    hyperid =

      `⁠24075⁠`

    name =

      `⁠theta75⁠`

    short.name =

      `⁠t75⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta76'
    hyperid =

      `⁠24076⁠`

    name =

      `⁠theta76⁠`

    short.name =

      `⁠t76⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta77'
    hyperid =

      `⁠24077⁠`

    name =

      `⁠theta77⁠`

    short.name =

      `⁠t77⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta78'
    hyperid =

      `⁠24078⁠`

    name =

      `⁠theta78⁠`

    short.name =

      `⁠t78⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta79'
    hyperid =

      `⁠24079⁠`

    name =

      `⁠theta79⁠`

    short.name =

      `⁠t79⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta80'
    hyperid =

      `⁠24080⁠`

    name =

      `⁠theta80⁠`

    short.name =

      `⁠t80⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta81'
    hyperid =

      `⁠24081⁠`

    name =

      `⁠theta81⁠`

    short.name =

      `⁠t81⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta82'
    hyperid =

      `⁠24082⁠`

    name =

      `⁠theta82⁠`

    short.name =

      `⁠t82⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta83'
    hyperid =

      `⁠24083⁠`

    name =

      `⁠theta83⁠`

    short.name =

      `⁠t83⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta84'
    hyperid =

      `⁠24084⁠`

    name =

      `⁠theta84⁠`

    short.name =

      `⁠t84⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta85'
    hyperid =

      `⁠24085⁠`

    name =

      `⁠theta85⁠`

    short.name =

      `⁠t85⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta86'
    hyperid =

      `⁠24086⁠`

    name =

      `⁠theta86⁠`

    short.name =

      `⁠t86⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta87'
    hyperid =

      `⁠24087⁠`

    name =

      `⁠theta87⁠`

    short.name =

      `⁠t87⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta88'
    hyperid =

      `⁠24088⁠`

    name =

      `⁠theta88⁠`

    short.name =

      `⁠t88⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta89'
    hyperid =

      `⁠24089⁠`

    name =

      `⁠theta89⁠`

    short.name =

      `⁠t89⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta90'
    hyperid =

      `⁠24090⁠`

    name =

      `⁠theta90⁠`

    short.name =

      `⁠t90⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta91'
    hyperid =

      `⁠24091⁠`

    name =

      `⁠theta91⁠`

    short.name =

      `⁠t91⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta92'
    hyperid =

      `⁠24092⁠`

    name =

      `⁠theta92⁠`

    short.name =

      `⁠t92⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta93'
    hyperid =

      `⁠24093⁠`

    name =

      `⁠theta93⁠`

    short.name =

      `⁠t93⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta94'
    hyperid =

      `⁠24094⁠`

    name =

      `⁠theta94⁠`

    short.name =

      `⁠t94⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta95'
    hyperid =

      `⁠24095⁠`

    name =

      `⁠theta95⁠`

    short.name =

      `⁠t95⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta96'
    hyperid =

      `⁠24096⁠`

    name =

      `⁠theta96⁠`

    short.name =

      `⁠t96⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta97'
    hyperid =

      `⁠24097⁠`

    name =

      `⁠theta97⁠`

    short.name =

      `⁠t97⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta98'
    hyperid =

      `⁠24098⁠`

    name =

      `⁠theta98⁠`

    short.name =

      `⁠t98⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta99'
    hyperid =

      `⁠24099⁠`

    name =

      `⁠theta99⁠`

    short.name =

      `⁠t99⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta100'
    hyperid =

      `⁠24100⁠`

    name =

      `⁠theta100⁠`

    short.name =

      `⁠t100⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

Model 'iid1d'.
  Properties:
    doc =

      `⁠Gaussian random effect in dim=1 with Wishart prior⁠`

    constr =

      `⁠FALSE⁠`

    nrow.ncol =

      `⁠FALSE⁠`

    augmented =

      `⁠FALSE⁠`

    aug.factor =

      `⁠1⁠`

    aug.constr =

      `⁠NULL⁠`

    n.div.by =

      `⁠NULL⁠`

    n.required =

      `⁠FALSE⁠`

    set.default.values =

      `⁠TRUE⁠`

    pdf =

      `⁠iid123d⁠`

  Number of hyperparmeters is 1.

  Hyperparameter 'theta'
    hyperid =

      `⁠25001⁠`

    name =

      `⁠precision⁠`

    short.name =

      `⁠prec⁠`

    initial =

      `⁠4⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠wishart1d⁠`

    param =

      `⁠2 1e-04⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

Model 'iid2d'.
  Properties:
    doc =

      `⁠Gaussian random effect in dim=2 with Wishart prior⁠`

    constr =

      `⁠FALSE⁠`

    nrow.ncol =

      `⁠FALSE⁠`

    augmented =

      `⁠TRUE⁠`

    aug.factor =

      `⁠1⁠`

    aug.constr =

      `⁠1 2⁠`

    n.div.by =

      `⁠2⁠`

    n.required =

      `⁠TRUE⁠`

    set.default.values =

      `⁠TRUE⁠`

    pdf =

      `⁠iid123d⁠`

  Number of hyperparmeters is 3.

  Hyperparameter 'theta1'
    hyperid =

      `⁠26001⁠`

    name =

      `⁠log precision1⁠`

    short.name =

      `⁠prec1⁠`

    initial =

      `⁠4⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠wishart2d⁠`

    param =

      `⁠4 1 1 0⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠26002⁠`

    name =

      `⁠log precision2⁠`

    short.name =

      `⁠prec2⁠`

    initial =

      `⁠4⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta3'
    hyperid =

      `⁠26003⁠`

    name =

      `⁠logit correlation⁠`

    short.name =

      `⁠cor⁠`

    initial =

      `⁠4⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) log((1 + x) / (1 - x))⁠`

    from.theta =

      `⁠function(x) 2 * exp(x) / (1 + exp(x)) - 1⁠`

Model 'iid3d'.
  Properties:
    doc =

      `⁠Gaussian random effect in dim=3 with Wishart prior⁠`

    constr =

      `⁠FALSE⁠`

    nrow.ncol =

      `⁠FALSE⁠`

    augmented =

      `⁠TRUE⁠`

    aug.factor =

      `⁠1⁠`

    aug.constr =

      `⁠1 2 3⁠`

    n.div.by =

      `⁠3⁠`

    n.required =

      `⁠TRUE⁠`

    set.default.values =

      `⁠TRUE⁠`

    pdf =

      `⁠iid123d⁠`

  Number of hyperparmeters is 6.

  Hyperparameter 'theta1'
    hyperid =

      `⁠27001⁠`

    name =

      `⁠log precision1⁠`

    short.name =

      `⁠prec1⁠`

    initial =

      `⁠4⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠wishart3d⁠`

    param =

      `⁠7 1 1 1 0 0 0⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠27002⁠`

    name =

      `⁠log precision2⁠`

    short.name =

      `⁠prec2⁠`

    initial =

      `⁠4⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta3'
    hyperid =

      `⁠27003⁠`

    name =

      `⁠log precision3⁠`

    short.name =

      `⁠prec3⁠`

    initial =

      `⁠4⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta4'
    hyperid =

      `⁠27004⁠`

    name =

      `⁠logit correlation12⁠`

    short.name =

      `⁠cor12⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) log((1 + x) / (1 - x))⁠`

    from.theta =

      `⁠function(x) 2 * exp(x) / (1 + exp(x)) - 1⁠`

  Hyperparameter 'theta5'
    hyperid =

      `⁠27005⁠`

    name =

      `⁠logit correlation13⁠`

    short.name =

      `⁠cor13⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) log((1 + x) / (1 - x))⁠`

    from.theta =

      `⁠function(x) 2 * exp(x) / (1 + exp(x)) - 1⁠`

  Hyperparameter 'theta6'
    hyperid =

      `⁠27006⁠`

    name =

      `⁠logit correlation23⁠`

    short.name =

      `⁠cor23⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) log((1 + x) / (1 - x))⁠`

    from.theta =

      `⁠function(x) 2 * exp(x) / (1 + exp(x)) - 1⁠`

Model 'iid4d'.
  Properties:
    doc =

      `⁠Gaussian random effect in dim=4 with Wishart prior⁠`

    constr =

      `⁠FALSE⁠`

    nrow.ncol =

      `⁠FALSE⁠`

    augmented =

      `⁠TRUE⁠`

    aug.factor =

      `⁠1⁠`

    aug.constr =

      `⁠1 2 3 4⁠`

    n.div.by =

      `⁠4⁠`

    n.required =

      `⁠TRUE⁠`

    set.default.values =

      `⁠TRUE⁠`

    pdf =

      `⁠iid123d⁠`

  Number of hyperparmeters is 10.

  Hyperparameter 'theta1'
    hyperid =

      `⁠28001⁠`

    name =

      `⁠log precision1⁠`

    short.name =

      `⁠prec1⁠`

    initial =

      `⁠4⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠wishart4d⁠`

    param =

      `⁠11 1 1 1 1 0 0 0 0 0 0⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠28002⁠`

    name =

      `⁠log precision2⁠`

    short.name =

      `⁠prec2⁠`

    initial =

      `⁠4⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta3'
    hyperid =

      `⁠28003⁠`

    name =

      `⁠log precision3⁠`

    short.name =

      `⁠prec3⁠`

    initial =

      `⁠4⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta4'
    hyperid =

      `⁠28004⁠`

    name =

      `⁠log precision4⁠`

    short.name =

      `⁠prec4⁠`

    initial =

      `⁠4⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta5'
    hyperid =

      `⁠28005⁠`

    name =

      `⁠logit correlation12⁠`

    short.name =

      `⁠cor12⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) log((1 + x) / (1 - x))⁠`

    from.theta =

      `⁠function(x) 2 * exp(x) / (1 + exp(x)) - 1⁠`

  Hyperparameter 'theta6'
    hyperid =

      `⁠28006⁠`

    name =

      `⁠logit correlation13⁠`

    short.name =

      `⁠cor13⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) log((1 + x) / (1 - x))⁠`

    from.theta =

      `⁠function(x) 2 * exp(x) / (1 + exp(x)) - 1⁠`

  Hyperparameter 'theta7'
    hyperid =

      `⁠28007⁠`

    name =

      `⁠logit correlation14⁠`

    short.name =

      `⁠cor14⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) log((1 + x) / (1 - x))⁠`

    from.theta =

      `⁠function(x) 2 * exp(x) / (1 + exp(x)) - 1⁠`

  Hyperparameter 'theta8'
    hyperid =

      `⁠28008⁠`

    name =

      `⁠logit correlation23⁠`

    short.name =

      `⁠cor23⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) log((1 + x) / (1 - x))⁠`

    from.theta =

      `⁠function(x) 2 * exp(x) / (1 + exp(x)) - 1⁠`

  Hyperparameter 'theta9'
    hyperid =

      `⁠28009⁠`

    name =

      `⁠logit correlation24⁠`

    short.name =

      `⁠cor24⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) log((1 + x) / (1 - x))⁠`

    from.theta =

      `⁠function(x) 2 * exp(x) / (1 + exp(x)) - 1⁠`

  Hyperparameter 'theta10'
    hyperid =

      `⁠28010⁠`

    name =

      `⁠logit correlation34⁠`

    short.name =

      `⁠cor34⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) log((1 + x) / (1 - x))⁠`

    from.theta =

      `⁠function(x) 2 * exp(x) / (1 + exp(x)) - 1⁠`

Model 'iid5d'.
  Properties:
    doc =

      `⁠Gaussian random effect in dim=5 with Wishart prior⁠`

    constr =

      `⁠FALSE⁠`

    nrow.ncol =

      `⁠FALSE⁠`

    augmented =

      `⁠TRUE⁠`

    aug.factor =

      `⁠1⁠`

    aug.constr =

      `⁠1 2 3 4 5⁠`

    n.div.by =

      `⁠5⁠`

    n.required =

      `⁠TRUE⁠`

    set.default.values =

      `⁠TRUE⁠`

    pdf =

      `⁠iid123d⁠`

  Number of hyperparmeters is 15.

  Hyperparameter 'theta1'
    hyperid =

      `⁠29001⁠`

    name =

      `⁠log precision1⁠`

    short.name =

      `⁠prec1⁠`

    initial =

      `⁠4⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠wishart5d⁠`

    param =

      `⁠16 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠29002⁠`

    name =

      `⁠log precision2⁠`

    short.name =

      `⁠prec2⁠`

    initial =

      `⁠4⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta3'
    hyperid =

      `⁠29003⁠`

    name =

      `⁠log precision3⁠`

    short.name =

      `⁠prec3⁠`

    initial =

      `⁠4⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta4'
    hyperid =

      `⁠29004⁠`

    name =

      `⁠log precision4⁠`

    short.name =

      `⁠prec4⁠`

    initial =

      `⁠4⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta5'
    hyperid =

      `⁠29005⁠`

    name =

      `⁠log precision5⁠`

    short.name =

      `⁠prec5⁠`

    initial =

      `⁠4⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta6'
    hyperid =

      `⁠29006⁠`

    name =

      `⁠logit correlation12⁠`

    short.name =

      `⁠cor12⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) log((1 + x) / (1 - x))⁠`

    from.theta =

      `⁠function(x) 2 * exp(x) / (1 + exp(x)) - 1⁠`

  Hyperparameter 'theta7'
    hyperid =

      `⁠29007⁠`

    name =

      `⁠logit correlation13⁠`

    short.name =

      `⁠cor13⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) log((1 + x) / (1 - x))⁠`

    from.theta =

      `⁠function(x) 2 * exp(x) / (1 + exp(x)) - 1⁠`

  Hyperparameter 'theta8'
    hyperid =

      `⁠29008⁠`

    name =

      `⁠logit correlation14⁠`

    short.name =

      `⁠cor14⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) log((1 + x) / (1 - x))⁠`

    from.theta =

      `⁠function(x) 2 * exp(x) / (1 + exp(x)) - 1⁠`

  Hyperparameter 'theta9'
    hyperid =

      `⁠29009⁠`

    name =

      `⁠logit correlation15⁠`

    short.name =

      `⁠cor15⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) log((1 + x) / (1 - x))⁠`

    from.theta =

      `⁠function(x) 2 * exp(x) / (1 + exp(x)) - 1⁠`

  Hyperparameter 'theta10'
    hyperid =

      `⁠29010⁠`

    name =

      `⁠logit correlation23⁠`

    short.name =

      `⁠cor23⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) log((1 + x) / (1 - x))⁠`

    from.theta =

      `⁠function(x) 2 * exp(x) / (1 + exp(x)) - 1⁠`

  Hyperparameter 'theta11'
    hyperid =

      `⁠29011⁠`

    name =

      `⁠logit correlation24⁠`

    short.name =

      `⁠cor24⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) log((1 + x) / (1 - x))⁠`

    from.theta =

      `⁠function(x) 2 * exp(x) / (1 + exp(x)) - 1⁠`

  Hyperparameter 'theta12'
    hyperid =

      `⁠29012⁠`

    name =

      `⁠logit correlation25⁠`

    short.name =

      `⁠cor25⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) log((1 + x) / (1 - x))⁠`

    from.theta =

      `⁠function(x) 2 * exp(x) / (1 + exp(x)) - 1⁠`

  Hyperparameter 'theta13'
    hyperid =

      `⁠29013⁠`

    name =

      `⁠logit correlation34⁠`

    short.name =

      `⁠cor34⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) log((1 + x) / (1 - x))⁠`

    from.theta =

      `⁠function(x) 2 * exp(x) / (1 + exp(x)) - 1⁠`

  Hyperparameter 'theta14'
    hyperid =

      `⁠29014⁠`

    name =

      `⁠logit correlation35⁠`

    short.name =

      `⁠cor35⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) log((1 + x) / (1 - x))⁠`

    from.theta =

      `⁠function(x) 2 * exp(x) / (1 + exp(x)) - 1⁠`

  Hyperparameter 'theta15'
    hyperid =

      `⁠29015⁠`

    name =

      `⁠logit correlation45⁠`

    short.name =

      `⁠cor45⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) log((1 + x) / (1 - x))⁠`

    from.theta =

      `⁠function(x) 2 * exp(x) / (1 + exp(x)) - 1⁠`

Model 'iidkd'.
  Properties:
    doc =

      `⁠Gaussian random effect in dim=k with Wishart prior⁠`

    constr =

      `⁠FALSE⁠`

    nrow.ncol =

      `⁠FALSE⁠`

    augmented =

      `⁠TRUE⁠`

    aug.factor =

      `⁠1⁠`

    aug.constr =

      `⁠1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24⁠`

    n.div.by =

      `⁠-1⁠`

    n.required =

      `⁠TRUE⁠`

    set.default.values =

      `⁠TRUE⁠`

    pdf =

      `⁠iidkd⁠`

  Number of hyperparmeters is 300.

  Hyperparameter 'theta1'
    hyperid =

      `⁠29101⁠`

    name =

      `⁠theta1⁠`

    short.name =

      `⁠theta1⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠wishartkd⁠`

    param =

      `⁠30 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576 1048576⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠29102⁠`

    name =

      `⁠theta2⁠`

    short.name =

      `⁠theta2⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta3'
    hyperid =

      `⁠29103⁠`

    name =

      `⁠theta3⁠`

    short.name =

      `⁠theta3⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta4'
    hyperid =

      `⁠29104⁠`

    name =

      `⁠theta4⁠`

    short.name =

      `⁠theta4⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta5'
    hyperid =

      `⁠29105⁠`

    name =

      `⁠theta5⁠`

    short.name =

      `⁠theta5⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta6'
    hyperid =

      `⁠29106⁠`

    name =

      `⁠theta6⁠`

    short.name =

      `⁠theta6⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta7'
    hyperid =

      `⁠29107⁠`

    name =

      `⁠theta7⁠`

    short.name =

      `⁠theta7⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta8'
    hyperid =

      `⁠29108⁠`

    name =

      `⁠theta8⁠`

    short.name =

      `⁠theta8⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta9'
    hyperid =

      `⁠29109⁠`

    name =

      `⁠theta9⁠`

    short.name =

      `⁠theta9⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta10'
    hyperid =

      `⁠29110⁠`

    name =

      `⁠theta10⁠`

    short.name =

      `⁠theta10⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta11'
    hyperid =

      `⁠29111⁠`

    name =

      `⁠theta11⁠`

    short.name =

      `⁠theta11⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta12'
    hyperid =

      `⁠29112⁠`

    name =

      `⁠theta12⁠`

    short.name =

      `⁠theta12⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta13'
    hyperid =

      `⁠29113⁠`

    name =

      `⁠theta13⁠`

    short.name =

      `⁠theta13⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta14'
    hyperid =

      `⁠29114⁠`

    name =

      `⁠theta14⁠`

    short.name =

      `⁠theta14⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta15'
    hyperid =

      `⁠29115⁠`

    name =

      `⁠theta15⁠`

    short.name =

      `⁠theta15⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta16'
    hyperid =

      `⁠29116⁠`

    name =

      `⁠theta16⁠`

    short.name =

      `⁠theta16⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta17'
    hyperid =

      `⁠29117⁠`

    name =

      `⁠theta17⁠`

    short.name =

      `⁠theta17⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta18'
    hyperid =

      `⁠29118⁠`

    name =

      `⁠theta18⁠`

    short.name =

      `⁠theta18⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta19'
    hyperid =

      `⁠29119⁠`

    name =

      `⁠theta19⁠`

    short.name =

      `⁠theta19⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta20'
    hyperid =

      `⁠29120⁠`

    name =

      `⁠theta20⁠`

    short.name =

      `⁠theta20⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta21'
    hyperid =

      `⁠29121⁠`

    name =

      `⁠theta21⁠`

    short.name =

      `⁠theta21⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta22'
    hyperid =

      `⁠29122⁠`

    name =

      `⁠theta22⁠`

    short.name =

      `⁠theta22⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta23'
    hyperid =

      `⁠29123⁠`

    name =

      `⁠theta23⁠`

    short.name =

      `⁠theta23⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta24'
    hyperid =

      `⁠29124⁠`

    name =

      `⁠theta24⁠`

    short.name =

      `⁠theta24⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta25'
    hyperid =

      `⁠29125⁠`

    name =

      `⁠theta25⁠`

    short.name =

      `⁠theta25⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta26'
    hyperid =

      `⁠29126⁠`

    name =

      `⁠theta26⁠`

    short.name =

      `⁠theta26⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta27'
    hyperid =

      `⁠29127⁠`

    name =

      `⁠theta27⁠`

    short.name =

      `⁠theta27⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta28'
    hyperid =

      `⁠29128⁠`

    name =

      `⁠theta28⁠`

    short.name =

      `⁠theta28⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta29'
    hyperid =

      `⁠29129⁠`

    name =

      `⁠theta29⁠`

    short.name =

      `⁠theta29⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta30'
    hyperid =

      `⁠29130⁠`

    name =

      `⁠theta30⁠`

    short.name =

      `⁠theta30⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta31'
    hyperid =

      `⁠29131⁠`

    name =

      `⁠theta31⁠`

    short.name =

      `⁠theta31⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta32'
    hyperid =

      `⁠29132⁠`

    name =

      `⁠theta32⁠`

    short.name =

      `⁠theta32⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta33'
    hyperid =

      `⁠29133⁠`

    name =

      `⁠theta33⁠`

    short.name =

      `⁠theta33⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta34'
    hyperid =

      `⁠29134⁠`

    name =

      `⁠theta34⁠`

    short.name =

      `⁠theta34⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta35'
    hyperid =

      `⁠29135⁠`

    name =

      `⁠theta35⁠`

    short.name =

      `⁠theta35⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta36'
    hyperid =

      `⁠29136⁠`

    name =

      `⁠theta36⁠`

    short.name =

      `⁠theta36⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta37'
    hyperid =

      `⁠29137⁠`

    name =

      `⁠theta37⁠`

    short.name =

      `⁠theta37⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta38'
    hyperid =

      `⁠29138⁠`

    name =

      `⁠theta38⁠`

    short.name =

      `⁠theta38⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta39'
    hyperid =

      `⁠29139⁠`

    name =

      `⁠theta39⁠`

    short.name =

      `⁠theta39⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta40'
    hyperid =

      `⁠29140⁠`

    name =

      `⁠theta40⁠`

    short.name =

      `⁠theta40⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta41'
    hyperid =

      `⁠29141⁠`

    name =

      `⁠theta41⁠`

    short.name =

      `⁠theta41⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta42'
    hyperid =

      `⁠29142⁠`

    name =

      `⁠theta42⁠`

    short.name =

      `⁠theta42⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta43'
    hyperid =

      `⁠29143⁠`

    name =

      `⁠theta43⁠`

    short.name =

      `⁠theta43⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta44'
    hyperid =

      `⁠29144⁠`

    name =

      `⁠theta44⁠`

    short.name =

      `⁠theta44⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta45'
    hyperid =

      `⁠29145⁠`

    name =

      `⁠theta45⁠`

    short.name =

      `⁠theta45⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta46'
    hyperid =

      `⁠29146⁠`

    name =

      `⁠theta46⁠`

    short.name =

      `⁠theta46⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta47'
    hyperid =

      `⁠29147⁠`

    name =

      `⁠theta47⁠`

    short.name =

      `⁠theta47⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta48'
    hyperid =

      `⁠29148⁠`

    name =

      `⁠theta48⁠`

    short.name =

      `⁠theta48⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta49'
    hyperid =

      `⁠29149⁠`

    name =

      `⁠theta49⁠`

    short.name =

      `⁠theta49⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta50'
    hyperid =

      `⁠29150⁠`

    name =

      `⁠theta50⁠`

    short.name =

      `⁠theta50⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta51'
    hyperid =

      `⁠29151⁠`

    name =

      `⁠theta51⁠`

    short.name =

      `⁠theta51⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta52'
    hyperid =

      `⁠29152⁠`

    name =

      `⁠theta52⁠`

    short.name =

      `⁠theta52⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta53'
    hyperid =

      `⁠29153⁠`

    name =

      `⁠theta53⁠`

    short.name =

      `⁠theta53⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta54'
    hyperid =

      `⁠29154⁠`

    name =

      `⁠theta54⁠`

    short.name =

      `⁠theta54⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta55'
    hyperid =

      `⁠29155⁠`

    name =

      `⁠theta55⁠`

    short.name =

      `⁠theta55⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta56'
    hyperid =

      `⁠29156⁠`

    name =

      `⁠theta56⁠`

    short.name =

      `⁠theta56⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta57'
    hyperid =

      `⁠29157⁠`

    name =

      `⁠theta57⁠`

    short.name =

      `⁠theta57⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta58'
    hyperid =

      `⁠29158⁠`

    name =

      `⁠theta58⁠`

    short.name =

      `⁠theta58⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta59'
    hyperid =

      `⁠29159⁠`

    name =

      `⁠theta59⁠`

    short.name =

      `⁠theta59⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta60'
    hyperid =

      `⁠29160⁠`

    name =

      `⁠theta60⁠`

    short.name =

      `⁠theta60⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta61'
    hyperid =

      `⁠29161⁠`

    name =

      `⁠theta61⁠`

    short.name =

      `⁠theta61⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta62'
    hyperid =

      `⁠29162⁠`

    name =

      `⁠theta62⁠`

    short.name =

      `⁠theta62⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta63'
    hyperid =

      `⁠29163⁠`

    name =

      `⁠theta63⁠`

    short.name =

      `⁠theta63⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta64'
    hyperid =

      `⁠29164⁠`

    name =

      `⁠theta64⁠`

    short.name =

      `⁠theta64⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta65'
    hyperid =

      `⁠29165⁠`

    name =

      `⁠theta65⁠`

    short.name =

      `⁠theta65⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta66'
    hyperid =

      `⁠29166⁠`

    name =

      `⁠theta66⁠`

    short.name =

      `⁠theta66⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta67'
    hyperid =

      `⁠29167⁠`

    name =

      `⁠theta67⁠`

    short.name =

      `⁠theta67⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta68'
    hyperid =

      `⁠29168⁠`

    name =

      `⁠theta68⁠`

    short.name =

      `⁠theta68⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta69'
    hyperid =

      `⁠29169⁠`

    name =

      `⁠theta69⁠`

    short.name =

      `⁠theta69⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta70'
    hyperid =

      `⁠29170⁠`

    name =

      `⁠theta70⁠`

    short.name =

      `⁠theta70⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta71'
    hyperid =

      `⁠29171⁠`

    name =

      `⁠theta71⁠`

    short.name =

      `⁠theta71⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta72'
    hyperid =

      `⁠29172⁠`

    name =

      `⁠theta72⁠`

    short.name =

      `⁠theta72⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta73'
    hyperid =

      `⁠29173⁠`

    name =

      `⁠theta73⁠`

    short.name =

      `⁠theta73⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta74'
    hyperid =

      `⁠29174⁠`

    name =

      `⁠theta74⁠`

    short.name =

      `⁠theta74⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta75'
    hyperid =

      `⁠29175⁠`

    name =

      `⁠theta75⁠`

    short.name =

      `⁠theta75⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta76'
    hyperid =

      `⁠29176⁠`

    name =

      `⁠theta76⁠`

    short.name =

      `⁠theta76⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta77'
    hyperid =

      `⁠29177⁠`

    name =

      `⁠theta77⁠`

    short.name =

      `⁠theta77⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta78'
    hyperid =

      `⁠29178⁠`

    name =

      `⁠theta78⁠`

    short.name =

      `⁠theta78⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta79'
    hyperid =

      `⁠29179⁠`

    name =

      `⁠theta79⁠`

    short.name =

      `⁠theta79⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta80'
    hyperid =

      `⁠29180⁠`

    name =

      `⁠theta80⁠`

    short.name =

      `⁠theta80⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta81'
    hyperid =

      `⁠29181⁠`

    name =

      `⁠theta81⁠`

    short.name =

      `⁠theta81⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta82'
    hyperid =

      `⁠29182⁠`

    name =

      `⁠theta82⁠`

    short.name =

      `⁠theta82⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta83'
    hyperid =

      `⁠29183⁠`

    name =

      `⁠theta83⁠`

    short.name =

      `⁠theta83⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta84'
    hyperid =

      `⁠29184⁠`

    name =

      `⁠theta84⁠`

    short.name =

      `⁠theta84⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta85'
    hyperid =

      `⁠29185⁠`

    name =

      `⁠theta85⁠`

    short.name =

      `⁠theta85⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta86'
    hyperid =

      `⁠29186⁠`

    name =

      `⁠theta86⁠`

    short.name =

      `⁠theta86⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta87'
    hyperid =

      `⁠29187⁠`

    name =

      `⁠theta87⁠`

    short.name =

      `⁠theta87⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta88'
    hyperid =

      `⁠29188⁠`

    name =

      `⁠theta88⁠`

    short.name =

      `⁠theta88⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta89'
    hyperid =

      `⁠29189⁠`

    name =

      `⁠theta89⁠`

    short.name =

      `⁠theta89⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta90'
    hyperid =

      `⁠29190⁠`

    name =

      `⁠theta90⁠`

    short.name =

      `⁠theta90⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta91'
    hyperid =

      `⁠29191⁠`

    name =

      `⁠theta91⁠`

    short.name =

      `⁠theta91⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta92'
    hyperid =

      `⁠29192⁠`

    name =

      `⁠theta92⁠`

    short.name =

      `⁠theta92⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta93'
    hyperid =

      `⁠29193⁠`

    name =

      `⁠theta93⁠`

    short.name =

      `⁠theta93⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta94'
    hyperid =

      `⁠29194⁠`

    name =

      `⁠theta94⁠`

    short.name =

      `⁠theta94⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta95'
    hyperid =

      `⁠29195⁠`

    name =

      `⁠theta95⁠`

    short.name =

      `⁠theta95⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta96'
    hyperid =

      `⁠29196⁠`

    name =

      `⁠theta96⁠`

    short.name =

      `⁠theta96⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta97'
    hyperid =

      `⁠29197⁠`

    name =

      `⁠theta97⁠`

    short.name =

      `⁠theta97⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta98'
    hyperid =

      `⁠29198⁠`

    name =

      `⁠theta98⁠`

    short.name =

      `⁠theta98⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta99'
    hyperid =

      `⁠29199⁠`

    name =

      `⁠theta99⁠`

    short.name =

      `⁠theta99⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta100'
    hyperid =

      `⁠29200⁠`

    name =

      `⁠theta100⁠`

    short.name =

      `⁠theta100⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta101'
    hyperid =

      `⁠29201⁠`

    name =

      `⁠theta101⁠`

    short.name =

      `⁠theta101⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta102'
    hyperid =

      `⁠29202⁠`

    name =

      `⁠theta102⁠`

    short.name =

      `⁠theta102⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta103'
    hyperid =

      `⁠29203⁠`

    name =

      `⁠theta103⁠`

    short.name =

      `⁠theta103⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta104'
    hyperid =

      `⁠29204⁠`

    name =

      `⁠theta104⁠`

    short.name =

      `⁠theta104⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta105'
    hyperid =

      `⁠29205⁠`

    name =

      `⁠theta105⁠`

    short.name =

      `⁠theta105⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta106'
    hyperid =

      `⁠29206⁠`

    name =

      `⁠theta106⁠`

    short.name =

      `⁠theta106⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta107'
    hyperid =

      `⁠29207⁠`

    name =

      `⁠theta107⁠`

    short.name =

      `⁠theta107⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta108'
    hyperid =

      `⁠29208⁠`

    name =

      `⁠theta108⁠`

    short.name =

      `⁠theta108⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta109'
    hyperid =

      `⁠29209⁠`

    name =

      `⁠theta109⁠`

    short.name =

      `⁠theta109⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta110'
    hyperid =

      `⁠29210⁠`

    name =

      `⁠theta110⁠`

    short.name =

      `⁠theta110⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta111'
    hyperid =

      `⁠29211⁠`

    name =

      `⁠theta111⁠`

    short.name =

      `⁠theta111⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta112'
    hyperid =

      `⁠29212⁠`

    name =

      `⁠theta112⁠`

    short.name =

      `⁠theta112⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta113'
    hyperid =

      `⁠29213⁠`

    name =

      `⁠theta113⁠`

    short.name =

      `⁠theta113⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta114'
    hyperid =

      `⁠29214⁠`

    name =

      `⁠theta114⁠`

    short.name =

      `⁠theta114⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta115'
    hyperid =

      `⁠29215⁠`

    name =

      `⁠theta115⁠`

    short.name =

      `⁠theta115⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta116'
    hyperid =

      `⁠29216⁠`

    name =

      `⁠theta116⁠`

    short.name =

      `⁠theta116⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta117'
    hyperid =

      `⁠29217⁠`

    name =

      `⁠theta117⁠`

    short.name =

      `⁠theta117⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta118'
    hyperid =

      `⁠29218⁠`

    name =

      `⁠theta118⁠`

    short.name =

      `⁠theta118⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta119'
    hyperid =

      `⁠29219⁠`

    name =

      `⁠theta119⁠`

    short.name =

      `⁠theta119⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta120'
    hyperid =

      `⁠29220⁠`

    name =

      `⁠theta120⁠`

    short.name =

      `⁠theta120⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta121'
    hyperid =

      `⁠29221⁠`

    name =

      `⁠theta121⁠`

    short.name =

      `⁠theta121⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta122'
    hyperid =

      `⁠29222⁠`

    name =

      `⁠theta122⁠`

    short.name =

      `⁠theta122⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta123'
    hyperid =

      `⁠29223⁠`

    name =

      `⁠theta123⁠`

    short.name =

      `⁠theta123⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta124'
    hyperid =

      `⁠29224⁠`

    name =

      `⁠theta124⁠`

    short.name =

      `⁠theta124⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta125'
    hyperid =

      `⁠29225⁠`

    name =

      `⁠theta125⁠`

    short.name =

      `⁠theta125⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta126'
    hyperid =

      `⁠29226⁠`

    name =

      `⁠theta126⁠`

    short.name =

      `⁠theta126⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta127'
    hyperid =

      `⁠29227⁠`

    name =

      `⁠theta127⁠`

    short.name =

      `⁠theta127⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta128'
    hyperid =

      `⁠29228⁠`

    name =

      `⁠theta128⁠`

    short.name =

      `⁠theta128⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta129'
    hyperid =

      `⁠29229⁠`

    name =

      `⁠theta129⁠`

    short.name =

      `⁠theta129⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta130'
    hyperid =

      `⁠29230⁠`

    name =

      `⁠theta130⁠`

    short.name =

      `⁠theta130⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta131'
    hyperid =

      `⁠29231⁠`

    name =

      `⁠theta131⁠`

    short.name =

      `⁠theta131⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta132'
    hyperid =

      `⁠29232⁠`

    name =

      `⁠theta132⁠`

    short.name =

      `⁠theta132⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta133'
    hyperid =

      `⁠29233⁠`

    name =

      `⁠theta133⁠`

    short.name =

      `⁠theta133⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta134'
    hyperid =

      `⁠29234⁠`

    name =

      `⁠theta134⁠`

    short.name =

      `⁠theta134⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta135'
    hyperid =

      `⁠29235⁠`

    name =

      `⁠theta135⁠`

    short.name =

      `⁠theta135⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta136'
    hyperid =

      `⁠29236⁠`

    name =

      `⁠theta136⁠`

    short.name =

      `⁠theta136⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta137'
    hyperid =

      `⁠29237⁠`

    name =

      `⁠theta137⁠`

    short.name =

      `⁠theta137⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta138'
    hyperid =

      `⁠29238⁠`

    name =

      `⁠theta138⁠`

    short.name =

      `⁠theta138⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta139'
    hyperid =

      `⁠29239⁠`

    name =

      `⁠theta139⁠`

    short.name =

      `⁠theta139⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta140'
    hyperid =

      `⁠29240⁠`

    name =

      `⁠theta140⁠`

    short.name =

      `⁠theta140⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta141'
    hyperid =

      `⁠29241⁠`

    name =

      `⁠theta141⁠`

    short.name =

      `⁠theta141⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta142'
    hyperid =

      `⁠29242⁠`

    name =

      `⁠theta142⁠`

    short.name =

      `⁠theta142⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta143'
    hyperid =

      `⁠29243⁠`

    name =

      `⁠theta143⁠`

    short.name =

      `⁠theta143⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta144'
    hyperid =

      `⁠29244⁠`

    name =

      `⁠theta144⁠`

    short.name =

      `⁠theta144⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta145'
    hyperid =

      `⁠29245⁠`

    name =

      `⁠theta145⁠`

    short.name =

      `⁠theta145⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta146'
    hyperid =

      `⁠29246⁠`

    name =

      `⁠theta146⁠`

    short.name =

      `⁠theta146⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta147'
    hyperid =

      `⁠29247⁠`

    name =

      `⁠theta147⁠`

    short.name =

      `⁠theta147⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta148'
    hyperid =

      `⁠29248⁠`

    name =

      `⁠theta148⁠`

    short.name =

      `⁠theta148⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta149'
    hyperid =

      `⁠29249⁠`

    name =

      `⁠theta149⁠`

    short.name =

      `⁠theta149⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta150'
    hyperid =

      `⁠29250⁠`

    name =

      `⁠theta150⁠`

    short.name =

      `⁠theta150⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta151'
    hyperid =

      `⁠29251⁠`

    name =

      `⁠theta151⁠`

    short.name =

      `⁠theta151⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta152'
    hyperid =

      `⁠29252⁠`

    name =

      `⁠theta152⁠`

    short.name =

      `⁠theta152⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta153'
    hyperid =

      `⁠29253⁠`

    name =

      `⁠theta153⁠`

    short.name =

      `⁠theta153⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta154'
    hyperid =

      `⁠29254⁠`

    name =

      `⁠theta154⁠`

    short.name =

      `⁠theta154⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta155'
    hyperid =

      `⁠29255⁠`

    name =

      `⁠theta155⁠`

    short.name =

      `⁠theta155⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta156'
    hyperid =

      `⁠29256⁠`

    name =

      `⁠theta156⁠`

    short.name =

      `⁠theta156⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta157'
    hyperid =

      `⁠29257⁠`

    name =

      `⁠theta157⁠`

    short.name =

      `⁠theta157⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta158'
    hyperid =

      `⁠29258⁠`

    name =

      `⁠theta158⁠`

    short.name =

      `⁠theta158⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta159'
    hyperid =

      `⁠29259⁠`

    name =

      `⁠theta159⁠`

    short.name =

      `⁠theta159⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta160'
    hyperid =

      `⁠29260⁠`

    name =

      `⁠theta160⁠`

    short.name =

      `⁠theta160⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta161'
    hyperid =

      `⁠29261⁠`

    name =

      `⁠theta161⁠`

    short.name =

      `⁠theta161⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta162'
    hyperid =

      `⁠29262⁠`

    name =

      `⁠theta162⁠`

    short.name =

      `⁠theta162⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta163'
    hyperid =

      `⁠29263⁠`

    name =

      `⁠theta163⁠`

    short.name =

      `⁠theta163⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta164'
    hyperid =

      `⁠29264⁠`

    name =

      `⁠theta164⁠`

    short.name =

      `⁠theta164⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta165'
    hyperid =

      `⁠29265⁠`

    name =

      `⁠theta165⁠`

    short.name =

      `⁠theta165⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta166'
    hyperid =

      `⁠29266⁠`

    name =

      `⁠theta166⁠`

    short.name =

      `⁠theta166⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta167'
    hyperid =

      `⁠29267⁠`

    name =

      `⁠theta167⁠`

    short.name =

      `⁠theta167⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta168'
    hyperid =

      `⁠29268⁠`

    name =

      `⁠theta168⁠`

    short.name =

      `⁠theta168⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta169'
    hyperid =

      `⁠29269⁠`

    name =

      `⁠theta169⁠`

    short.name =

      `⁠theta169⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta170'
    hyperid =

      `⁠29270⁠`

    name =

      `⁠theta170⁠`

    short.name =

      `⁠theta170⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta171'
    hyperid =

      `⁠29271⁠`

    name =

      `⁠theta171⁠`

    short.name =

      `⁠theta171⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta172'
    hyperid =

      `⁠29272⁠`

    name =

      `⁠theta172⁠`

    short.name =

      `⁠theta172⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta173'
    hyperid =

      `⁠29273⁠`

    name =

      `⁠theta173⁠`

    short.name =

      `⁠theta173⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta174'
    hyperid =

      `⁠29274⁠`

    name =

      `⁠theta174⁠`

    short.name =

      `⁠theta174⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta175'
    hyperid =

      `⁠29275⁠`

    name =

      `⁠theta175⁠`

    short.name =

      `⁠theta175⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta176'
    hyperid =

      `⁠29276⁠`

    name =

      `⁠theta176⁠`

    short.name =

      `⁠theta176⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta177'
    hyperid =

      `⁠29277⁠`

    name =

      `⁠theta177⁠`

    short.name =

      `⁠theta177⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta178'
    hyperid =

      `⁠29278⁠`

    name =

      `⁠theta178⁠`

    short.name =

      `⁠theta178⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta179'
    hyperid =

      `⁠29279⁠`

    name =

      `⁠theta179⁠`

    short.name =

      `⁠theta179⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta180'
    hyperid =

      `⁠29280⁠`

    name =

      `⁠theta180⁠`

    short.name =

      `⁠theta180⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta181'
    hyperid =

      `⁠29281⁠`

    name =

      `⁠theta181⁠`

    short.name =

      `⁠theta181⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta182'
    hyperid =

      `⁠29282⁠`

    name =

      `⁠theta182⁠`

    short.name =

      `⁠theta182⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta183'
    hyperid =

      `⁠29283⁠`

    name =

      `⁠theta183⁠`

    short.name =

      `⁠theta183⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta184'
    hyperid =

      `⁠29284⁠`

    name =

      `⁠theta184⁠`

    short.name =

      `⁠theta184⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta185'
    hyperid =

      `⁠29285⁠`

    name =

      `⁠theta185⁠`

    short.name =

      `⁠theta185⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta186'
    hyperid =

      `⁠29286⁠`

    name =

      `⁠theta186⁠`

    short.name =

      `⁠theta186⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta187'
    hyperid =

      `⁠29287⁠`

    name =

      `⁠theta187⁠`

    short.name =

      `⁠theta187⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta188'
    hyperid =

      `⁠29288⁠`

    name =

      `⁠theta188⁠`

    short.name =

      `⁠theta188⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta189'
    hyperid =

      `⁠29289⁠`

    name =

      `⁠theta189⁠`

    short.name =

      `⁠theta189⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta190'
    hyperid =

      `⁠29290⁠`

    name =

      `⁠theta190⁠`

    short.name =

      `⁠theta190⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta191'
    hyperid =

      `⁠29291⁠`

    name =

      `⁠theta191⁠`

    short.name =

      `⁠theta191⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta192'
    hyperid =

      `⁠29292⁠`

    name =

      `⁠theta192⁠`

    short.name =

      `⁠theta192⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta193'
    hyperid =

      `⁠29293⁠`

    name =

      `⁠theta193⁠`

    short.name =

      `⁠theta193⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta194'
    hyperid =

      `⁠29294⁠`

    name =

      `⁠theta194⁠`

    short.name =

      `⁠theta194⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta195'
    hyperid =

      `⁠29295⁠`

    name =

      `⁠theta195⁠`

    short.name =

      `⁠theta195⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta196'
    hyperid =

      `⁠29296⁠`

    name =

      `⁠theta196⁠`

    short.name =

      `⁠theta196⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta197'
    hyperid =

      `⁠29297⁠`

    name =

      `⁠theta197⁠`

    short.name =

      `⁠theta197⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta198'
    hyperid =

      `⁠29298⁠`

    name =

      `⁠theta198⁠`

    short.name =

      `⁠theta198⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta199'
    hyperid =

      `⁠29299⁠`

    name =

      `⁠theta199⁠`

    short.name =

      `⁠theta199⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta200'
    hyperid =

      `⁠29300⁠`

    name =

      `⁠theta200⁠`

    short.name =

      `⁠theta200⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta201'
    hyperid =

      `⁠29301⁠`

    name =

      `⁠theta201⁠`

    short.name =

      `⁠theta201⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta202'
    hyperid =

      `⁠29302⁠`

    name =

      `⁠theta202⁠`

    short.name =

      `⁠theta202⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta203'
    hyperid =

      `⁠29303⁠`

    name =

      `⁠theta203⁠`

    short.name =

      `⁠theta203⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta204'
    hyperid =

      `⁠29304⁠`

    name =

      `⁠theta204⁠`

    short.name =

      `⁠theta204⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta205'
    hyperid =

      `⁠29305⁠`

    name =

      `⁠theta205⁠`

    short.name =

      `⁠theta205⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta206'
    hyperid =

      `⁠29306⁠`

    name =

      `⁠theta206⁠`

    short.name =

      `⁠theta206⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta207'
    hyperid =

      `⁠29307⁠`

    name =

      `⁠theta207⁠`

    short.name =

      `⁠theta207⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta208'
    hyperid =

      `⁠29308⁠`

    name =

      `⁠theta208⁠`

    short.name =

      `⁠theta208⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta209'
    hyperid =

      `⁠29309⁠`

    name =

      `⁠theta209⁠`

    short.name =

      `⁠theta209⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta210'
    hyperid =

      `⁠29310⁠`

    name =

      `⁠theta210⁠`

    short.name =

      `⁠theta210⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta211'
    hyperid =

      `⁠29311⁠`

    name =

      `⁠theta211⁠`

    short.name =

      `⁠theta211⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta212'
    hyperid =

      `⁠29312⁠`

    name =

      `⁠theta212⁠`

    short.name =

      `⁠theta212⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta213'
    hyperid =

      `⁠29313⁠`

    name =

      `⁠theta213⁠`

    short.name =

      `⁠theta213⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta214'
    hyperid =

      `⁠29314⁠`

    name =

      `⁠theta214⁠`

    short.name =

      `⁠theta214⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta215'
    hyperid =

      `⁠29315⁠`

    name =

      `⁠theta215⁠`

    short.name =

      `⁠theta215⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta216'
    hyperid =

      `⁠29316⁠`

    name =

      `⁠theta216⁠`

    short.name =

      `⁠theta216⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta217'
    hyperid =

      `⁠29317⁠`

    name =

      `⁠theta217⁠`

    short.name =

      `⁠theta217⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta218'
    hyperid =

      `⁠29318⁠`

    name =

      `⁠theta218⁠`

    short.name =

      `⁠theta218⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta219'
    hyperid =

      `⁠29319⁠`

    name =

      `⁠theta219⁠`

    short.name =

      `⁠theta219⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta220'
    hyperid =

      `⁠29320⁠`

    name =

      `⁠theta220⁠`

    short.name =

      `⁠theta220⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta221'
    hyperid =

      `⁠29321⁠`

    name =

      `⁠theta221⁠`

    short.name =

      `⁠theta221⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta222'
    hyperid =

      `⁠29322⁠`

    name =

      `⁠theta222⁠`

    short.name =

      `⁠theta222⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta223'
    hyperid =

      `⁠29323⁠`

    name =

      `⁠theta223⁠`

    short.name =

      `⁠theta223⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta224'
    hyperid =

      `⁠29324⁠`

    name =

      `⁠theta224⁠`

    short.name =

      `⁠theta224⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta225'
    hyperid =

      `⁠29325⁠`

    name =

      `⁠theta225⁠`

    short.name =

      `⁠theta225⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta226'
    hyperid =

      `⁠29326⁠`

    name =

      `⁠theta226⁠`

    short.name =

      `⁠theta226⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta227'
    hyperid =

      `⁠29327⁠`

    name =

      `⁠theta227⁠`

    short.name =

      `⁠theta227⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta228'
    hyperid =

      `⁠29328⁠`

    name =

      `⁠theta228⁠`

    short.name =

      `⁠theta228⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta229'
    hyperid =

      `⁠29329⁠`

    name =

      `⁠theta229⁠`

    short.name =

      `⁠theta229⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta230'
    hyperid =

      `⁠29330⁠`

    name =

      `⁠theta230⁠`

    short.name =

      `⁠theta230⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta231'
    hyperid =

      `⁠29331⁠`

    name =

      `⁠theta231⁠`

    short.name =

      `⁠theta231⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta232'
    hyperid =

      `⁠29332⁠`

    name =

      `⁠theta232⁠`

    short.name =

      `⁠theta232⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta233'
    hyperid =

      `⁠29333⁠`

    name =

      `⁠theta233⁠`

    short.name =

      `⁠theta233⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta234'
    hyperid =

      `⁠29334⁠`

    name =

      `⁠theta234⁠`

    short.name =

      `⁠theta234⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta235'
    hyperid =

      `⁠29335⁠`

    name =

      `⁠theta235⁠`

    short.name =

      `⁠theta235⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta236'
    hyperid =

      `⁠29336⁠`

    name =

      `⁠theta236⁠`

    short.name =

      `⁠theta236⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta237'
    hyperid =

      `⁠29337⁠`

    name =

      `⁠theta237⁠`

    short.name =

      `⁠theta237⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta238'
    hyperid =

      `⁠29338⁠`

    name =

      `⁠theta238⁠`

    short.name =

      `⁠theta238⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta239'
    hyperid =

      `⁠29339⁠`

    name =

      `⁠theta239⁠`

    short.name =

      `⁠theta239⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta240'
    hyperid =

      `⁠29340⁠`

    name =

      `⁠theta240⁠`

    short.name =

      `⁠theta240⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta241'
    hyperid =

      `⁠29341⁠`

    name =

      `⁠theta241⁠`

    short.name =

      `⁠theta241⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta242'
    hyperid =

      `⁠29342⁠`

    name =

      `⁠theta242⁠`

    short.name =

      `⁠theta242⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta243'
    hyperid =

      `⁠29343⁠`

    name =

      `⁠theta243⁠`

    short.name =

      `⁠theta243⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta244'
    hyperid =

      `⁠29344⁠`

    name =

      `⁠theta244⁠`

    short.name =

      `⁠theta244⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta245'
    hyperid =

      `⁠29345⁠`

    name =

      `⁠theta245⁠`

    short.name =

      `⁠theta245⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta246'
    hyperid =

      `⁠29346⁠`

    name =

      `⁠theta246⁠`

    short.name =

      `⁠theta246⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta247'
    hyperid =

      `⁠29347⁠`

    name =

      `⁠theta247⁠`

    short.name =

      `⁠theta247⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta248'
    hyperid =

      `⁠29348⁠`

    name =

      `⁠theta248⁠`

    short.name =

      `⁠theta248⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta249'
    hyperid =

      `⁠29349⁠`

    name =

      `⁠theta249⁠`

    short.name =

      `⁠theta249⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta250'
    hyperid =

      `⁠29350⁠`

    name =

      `⁠theta250⁠`

    short.name =

      `⁠theta250⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta251'
    hyperid =

      `⁠29351⁠`

    name =

      `⁠theta251⁠`

    short.name =

      `⁠theta251⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta252'
    hyperid =

      `⁠29352⁠`

    name =

      `⁠theta252⁠`

    short.name =

      `⁠theta252⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta253'
    hyperid =

      `⁠29353⁠`

    name =

      `⁠theta253⁠`

    short.name =

      `⁠theta253⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta254'
    hyperid =

      `⁠29354⁠`

    name =

      `⁠theta254⁠`

    short.name =

      `⁠theta254⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta255'
    hyperid =

      `⁠29355⁠`

    name =

      `⁠theta255⁠`

    short.name =

      `⁠theta255⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta256'
    hyperid =

      `⁠29356⁠`

    name =

      `⁠theta256⁠`

    short.name =

      `⁠theta256⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta257'
    hyperid =

      `⁠29357⁠`

    name =

      `⁠theta257⁠`

    short.name =

      `⁠theta257⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta258'
    hyperid =

      `⁠29358⁠`

    name =

      `⁠theta258⁠`

    short.name =

      `⁠theta258⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta259'
    hyperid =

      `⁠29359⁠`

    name =

      `⁠theta259⁠`

    short.name =

      `⁠theta259⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta260'
    hyperid =

      `⁠29360⁠`

    name =

      `⁠theta260⁠`

    short.name =

      `⁠theta260⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta261'
    hyperid =

      `⁠29361⁠`

    name =

      `⁠theta261⁠`

    short.name =

      `⁠theta261⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta262'
    hyperid =

      `⁠29362⁠`

    name =

      `⁠theta262⁠`

    short.name =

      `⁠theta262⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta263'
    hyperid =

      `⁠29363⁠`

    name =

      `⁠theta263⁠`

    short.name =

      `⁠theta263⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta264'
    hyperid =

      `⁠29364⁠`

    name =

      `⁠theta264⁠`

    short.name =

      `⁠theta264⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta265'
    hyperid =

      `⁠29365⁠`

    name =

      `⁠theta265⁠`

    short.name =

      `⁠theta265⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta266'
    hyperid =

      `⁠29366⁠`

    name =

      `⁠theta266⁠`

    short.name =

      `⁠theta266⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta267'
    hyperid =

      `⁠29367⁠`

    name =

      `⁠theta267⁠`

    short.name =

      `⁠theta267⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta268'
    hyperid =

      `⁠29368⁠`

    name =

      `⁠theta268⁠`

    short.name =

      `⁠theta268⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta269'
    hyperid =

      `⁠29369⁠`

    name =

      `⁠theta269⁠`

    short.name =

      `⁠theta269⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta270'
    hyperid =

      `⁠29370⁠`

    name =

      `⁠theta270⁠`

    short.name =

      `⁠theta270⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta271'
    hyperid =

      `⁠29371⁠`

    name =

      `⁠theta271⁠`

    short.name =

      `⁠theta271⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta272'
    hyperid =

      `⁠29372⁠`

    name =

      `⁠theta272⁠`

    short.name =

      `⁠theta272⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta273'
    hyperid =

      `⁠29373⁠`

    name =

      `⁠theta273⁠`

    short.name =

      `⁠theta273⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta274'
    hyperid =

      `⁠29374⁠`

    name =

      `⁠theta274⁠`

    short.name =

      `⁠theta274⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta275'
    hyperid =

      `⁠29375⁠`

    name =

      `⁠theta275⁠`

    short.name =

      `⁠theta275⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta276'
    hyperid =

      `⁠29376⁠`

    name =

      `⁠theta276⁠`

    short.name =

      `⁠theta276⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta277'
    hyperid =

      `⁠29377⁠`

    name =

      `⁠theta277⁠`

    short.name =

      `⁠theta277⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta278'
    hyperid =

      `⁠29378⁠`

    name =

      `⁠theta278⁠`

    short.name =

      `⁠theta278⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta279'
    hyperid =

      `⁠29379⁠`

    name =

      `⁠theta279⁠`

    short.name =

      `⁠theta279⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta280'
    hyperid =

      `⁠29380⁠`

    name =

      `⁠theta280⁠`

    short.name =

      `⁠theta280⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta281'
    hyperid =

      `⁠29381⁠`

    name =

      `⁠theta281⁠`

    short.name =

      `⁠theta281⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta282'
    hyperid =

      `⁠29382⁠`

    name =

      `⁠theta282⁠`

    short.name =

      `⁠theta282⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta283'
    hyperid =

      `⁠29383⁠`

    name =

      `⁠theta283⁠`

    short.name =

      `⁠theta283⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta284'
    hyperid =

      `⁠29384⁠`

    name =

      `⁠theta284⁠`

    short.name =

      `⁠theta284⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta285'
    hyperid =

      `⁠29385⁠`

    name =

      `⁠theta285⁠`

    short.name =

      `⁠theta285⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta286'
    hyperid =

      `⁠29386⁠`

    name =

      `⁠theta286⁠`

    short.name =

      `⁠theta286⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta287'
    hyperid =

      `⁠29387⁠`

    name =

      `⁠theta287⁠`

    short.name =

      `⁠theta287⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta288'
    hyperid =

      `⁠29388⁠`

    name =

      `⁠theta288⁠`

    short.name =

      `⁠theta288⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta289'
    hyperid =

      `⁠29389⁠`

    name =

      `⁠theta289⁠`

    short.name =

      `⁠theta289⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta290'
    hyperid =

      `⁠29390⁠`

    name =

      `⁠theta290⁠`

    short.name =

      `⁠theta290⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta291'
    hyperid =

      `⁠29391⁠`

    name =

      `⁠theta291⁠`

    short.name =

      `⁠theta291⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta292'
    hyperid =

      `⁠29392⁠`

    name =

      `⁠theta292⁠`

    short.name =

      `⁠theta292⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta293'
    hyperid =

      `⁠29393⁠`

    name =

      `⁠theta293⁠`

    short.name =

      `⁠theta293⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta294'
    hyperid =

      `⁠29394⁠`

    name =

      `⁠theta294⁠`

    short.name =

      `⁠theta294⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta295'
    hyperid =

      `⁠29395⁠`

    name =

      `⁠theta295⁠`

    short.name =

      `⁠theta295⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta296'
    hyperid =

      `⁠29396⁠`

    name =

      `⁠theta296⁠`

    short.name =

      `⁠theta296⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta297'
    hyperid =

      `⁠29397⁠`

    name =

      `⁠theta297⁠`

    short.name =

      `⁠theta297⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta298'
    hyperid =

      `⁠29398⁠`

    name =

      `⁠theta298⁠`

    short.name =

      `⁠theta298⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta299'
    hyperid =

      `⁠29399⁠`

    name =

      `⁠theta299⁠`

    short.name =

      `⁠theta299⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta300'
    hyperid =

      `⁠29400⁠`

    name =

      `⁠theta300⁠`

    short.name =

      `⁠theta300⁠`

    initial =

      `⁠1048576⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

Model '2diid'.
  Properties:
    doc =

      `⁠(This model is obsolute)⁠`

    constr =

      `⁠FALSE⁠`

    nrow.ncol =

      `⁠FALSE⁠`

    augmented =

      `⁠FALSE⁠`

    aug.factor =

      `⁠1⁠`

    aug.constr =

      `⁠1 2⁠`

    n.div.by =

      `⁠2⁠`

    n.required =

      `⁠TRUE⁠`

    set.default.values =

      `⁠TRUE⁠`

    pdf =

      `⁠iid123d⁠`

  Number of hyperparmeters is 3.

  Hyperparameter 'theta1'
    hyperid =

      `⁠30001⁠`

    name =

      `⁠log precision1⁠`

    short.name =

      `⁠prec1⁠`

    initial =

      `⁠4⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 5e-05⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠30002⁠`

    name =

      `⁠log precision2⁠`

    short.name =

      `⁠prec2⁠`

    initial =

      `⁠4⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 5e-05⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta3'
    hyperid =

      `⁠30003⁠`

    name =

      `⁠correlation⁠`

    short.name =

      `⁠cor⁠`

    initial =

      `⁠4⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 0.15⁠`

    to.theta =

      `⁠function(x) log((1 + x) / (1 - x))⁠`

    from.theta =

      `⁠function(x) 2 * exp(x) / (1 + exp(x)) - 1⁠`

Model 'z'.
  Properties:
    doc =

      `⁠The z-model in a classical mixed model formulation⁠`

    constr =

      `⁠FALSE⁠`

    nrow.ncol =

      `⁠FALSE⁠`

    augmented =

      `⁠FALSE⁠`

    aug.factor =

      `⁠1⁠`

    aug.constr =

      `⁠NULL⁠`

    n.div.by =

      `⁠NULL⁠`

    n.required =

      `⁠TRUE⁠`

    set.default.values =

      `⁠TRUE⁠`

    pdf =

      `⁠z⁠`

  Number of hyperparmeters is 1.

  Hyperparameter 'theta'
    hyperid =

      `⁠31001⁠`

    name =

      `⁠log precision⁠`

    short.name =

      `⁠prec⁠`

    initial =

      `⁠4⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 5e-05⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

Model 'rw2d'.
  Properties:
    doc =

      `⁠Thin-plate spline model⁠`

    constr =

      `⁠TRUE⁠`

    nrow.ncol =

      `⁠TRUE⁠`

    augmented =

      `⁠FALSE⁠`

    aug.factor =

      `⁠1⁠`

    aug.constr =

      `⁠NULL⁠`

    n.div.by =

      `⁠NULL⁠`

    n.required =

      `⁠FALSE⁠`

    set.default.values =

      `⁠TRUE⁠`

    pdf =

      `⁠rw2d⁠`

  Number of hyperparmeters is 1.

  Hyperparameter 'theta'
    hyperid =

      `⁠32001⁠`

    name =

      `⁠log precision⁠`

    short.name =

      `⁠prec⁠`

    initial =

      `⁠4⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 5e-05⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

Model 'rw2diid'.
  Properties:
    doc =

      `⁠Thin-plate spline with iid noise⁠`

    constr =

      `⁠TRUE⁠`

    nrow.ncol =

      `⁠TRUE⁠`

    augmented =

      `⁠TRUE⁠`

    aug.factor =

      `⁠2⁠`

    aug.constr =

      `⁠2⁠`

    n.div.by =

      `⁠NULL⁠`

    n.required =

      `⁠FALSE⁠`

    set.default.values =

      `⁠TRUE⁠`

    pdf =

      `⁠rw2diid⁠`

  Number of hyperparmeters is 2.

  Hyperparameter 'theta1'
    hyperid =

      `⁠33001⁠`

    name =

      `⁠log precision⁠`

    short.name =

      `⁠prec⁠`

    prior =

      `⁠pc.prec⁠`

    param =

      `⁠1 0.01⁠`

    initial =

      `⁠4⁠`

    fixed =

      `⁠FALSE⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠33002⁠`

    name =

      `⁠logit phi⁠`

    short.name =

      `⁠phi⁠`

    prior =

      `⁠pc⁠`

    param =

      `⁠0.5 0.5⁠`

    initial =

      `⁠3⁠`

    fixed =

      `⁠FALSE⁠`

    to.theta =

      `⁠function(x) log(x / (1 - x))⁠`

    from.theta =

      `⁠function(x) exp(x) / (1 + exp(x))⁠`

Model 'slm'.
  Properties:
    doc =

      `⁠Spatial lag model⁠`

    constr =

      `⁠FALSE⁠`

    nrow.ncol =

      `⁠FALSE⁠`

    augmented =

      `⁠FALSE⁠`

    aug.factor =

      `⁠1⁠`

    aug.constr =

      `⁠NULL⁠`

    n.div.by =

      `⁠NULL⁠`

    n.required =

      `⁠TRUE⁠`

    set.default.values =

      `⁠TRUE⁠`

    pdf =

      `⁠slm⁠`

  Number of hyperparmeters is 2.

  Hyperparameter 'theta1'
    hyperid =

      `⁠34001⁠`

    name =

      `⁠log precision⁠`

    short.name =

      `⁠prec⁠`

    initial =

      `⁠4⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 5e-05⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠34002⁠`

    name =

      `⁠rho⁠`

    short.name =

      `⁠rho⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) log(x / (1 - x))⁠`

    from.theta =

      `⁠function(x) 1 / (1 + exp(-x))⁠`

Model 'matern2d'.
  Properties:
    doc =

      `⁠Matern covariance function on a regular grid⁠`

    constr =

      `⁠FALSE⁠`

    nrow.ncol =

      `⁠TRUE⁠`

    augmented =

      `⁠FALSE⁠`

    aug.factor =

      `⁠1⁠`

    aug.constr =

      `⁠NULL⁠`

    n.div.by =

      `⁠NULL⁠`

    n.required =

      `⁠FALSE⁠`

    set.default.values =

      `⁠TRUE⁠`

    pdf =

      `⁠matern2d⁠`

  Number of hyperparmeters is 2.

  Hyperparameter 'theta1'
    hyperid =

      `⁠35001⁠`

    name =

      `⁠log precision⁠`

    short.name =

      `⁠prec⁠`

    initial =

      `⁠4⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 5e-05⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠35002⁠`

    name =

      `⁠log range⁠`

    short.name =

      `⁠range⁠`

    initial =

      `⁠2⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 0.01⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

Model 'dmatern'.
  Properties:
    doc =

      `⁠Dense Matern field⁠`

    constr =

      `⁠FALSE⁠`

    nrow.ncol =

      `⁠FALSE⁠`

    augmented =

      `⁠FALSE⁠`

    aug.factor =

      `⁠1⁠`

    aug.constr =

      `⁠NULL⁠`

    n.div.by =

      `⁠NULL⁠`

    n.required =

      `⁠TRUE⁠`

    set.default.values =

      `⁠TRUE⁠`

    pdf =

      `⁠dmatern⁠`

  Number of hyperparmeters is 3.

  Hyperparameter 'theta1'
    hyperid =

      `⁠35101⁠`

    name =

      `⁠log precision⁠`

    short.name =

      `⁠prec⁠`

    initial =

      `⁠3⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠pc.prec⁠`

    param =

      `⁠1 0.01⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠35102⁠`

    name =

      `⁠log range⁠`

    short.name =

      `⁠range⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠pc.range⁠`

    param =

      `⁠1 0.5⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta3'
    hyperid =

      `⁠35103⁠`

    name =

      `⁠log nu⁠`

    short.name =

      `⁠nu⁠`

    initial =

      `⁠-0.693147180559945⁠`

    fixed =

      `⁠TRUE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠0.5 1⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

Model 'copy'.
  Properties:
    doc =

      `⁠Create a copy of a model component⁠`

    constr =

      `⁠FALSE⁠`

    nrow.ncol =

      `⁠FALSE⁠`

    augmented =

      `⁠FALSE⁠`

    aug.factor =

      `⁠1⁠`

    aug.constr =

      `⁠NULL⁠`

    n.div.by =

      `⁠NULL⁠`

    n.required =

      `⁠FALSE⁠`

    set.default.values =

      `⁠FALSE⁠`

    pdf =

      `⁠copy⁠`

  Number of hyperparmeters is 1.

  Hyperparameter 'theta'
    hyperid =

      `⁠36001⁠`

    name =

      `⁠beta⁠`

    short.name =

      `⁠b⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠TRUE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x, REPLACE.ME.low, REPLACE.ME.high) { if (all(is.infinite(c(low, high))) || low == high) { return(x) } else if (all(is.finite(c(low, high)))) { stopifnot(low < high) return(log(-(low - x) / (high - x))) } else if (is.finite(low) && is.infinite(high) && high > low) { return(log(x - low)) } else { stop("Condition not yet implemented") } }⁠`

    from.theta =

      `⁠function(x, REPLACE.ME.low, REPLACE.ME.high) { if (all(is.infinite(c(low, high))) || low == high) { return(x) } else if (all(is.finite(c(low, high)))) { stopifnot(low < high) return(low + exp(x) / (1 + exp(x)) * (high - low)) } else if (is.finite(low) && is.infinite(high) && high > low) { return(low + exp(x)) } else { stop("Condition not yet implemented") } }⁠`

Model 'scopy'.
  Properties:
    doc =

      `⁠Create a scopy of a model component⁠`

    constr =

      `⁠FALSE⁠`

    nrow.ncol =

      `⁠FALSE⁠`

    augmented =

      `⁠FALSE⁠`

    aug.factor =

      `⁠1⁠`

    aug.constr =

      `⁠NULL⁠`

    n.div.by =

      `⁠NULL⁠`

    n.required =

      `⁠FALSE⁠`

    set.default.values =

      `⁠FALSE⁠`

    pdf =

      `⁠scopy⁠`

  Number of hyperparmeters is 15.

  Hyperparameter 'theta1'
    hyperid =

      `⁠36101⁠`

    name =

      `⁠mean⁠`

    short.name =

      `⁠mean⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠36102⁠`

    name =

      `⁠slope⁠`

    short.name =

      `⁠slope⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta3'
    hyperid =

      `⁠36103⁠`

    name =

      `⁠spline.theta1⁠`

    short.name =

      `⁠spline⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠laplace⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta4'
    hyperid =

      `⁠36104⁠`

    name =

      `⁠spline.theta2⁠`

    short.name =

      `⁠spline2⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta5'
    hyperid =

      `⁠36105⁠`

    name =

      `⁠spline.theta3⁠`

    short.name =

      `⁠spline3⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta6'
    hyperid =

      `⁠36106⁠`

    name =

      `⁠spline.theta4⁠`

    short.name =

      `⁠spline4⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta7'
    hyperid =

      `⁠36107⁠`

    name =

      `⁠spline.theta5⁠`

    short.name =

      `⁠spline5⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta8'
    hyperid =

      `⁠36108⁠`

    name =

      `⁠spline.theta6⁠`

    short.name =

      `⁠spline6⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta9'
    hyperid =

      `⁠36109⁠`

    name =

      `⁠spline.theta7⁠`

    short.name =

      `⁠spline7⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta10'
    hyperid =

      `⁠36110⁠`

    name =

      `⁠spline.theta8⁠`

    short.name =

      `⁠spline8⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta11'
    hyperid =

      `⁠36111⁠`

    name =

      `⁠spline.theta9⁠`

    short.name =

      `⁠spline9⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta12'
    hyperid =

      `⁠36112⁠`

    name =

      `⁠spline.theta10⁠`

    short.name =

      `⁠spline10⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta13'
    hyperid =

      `⁠36113⁠`

    name =

      `⁠spline.theta11⁠`

    short.name =

      `⁠spline11⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta14'
    hyperid =

      `⁠36114⁠`

    name =

      `⁠spline.theta12⁠`

    short.name =

      `⁠spline12⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta15'
    hyperid =

      `⁠36115⁠`

    name =

      `⁠spline.theta13⁠`

    short.name =

      `⁠spline13⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

Model 'clinear'.
  Properties:
    doc =

      `⁠Constrained linear effect⁠`

    constr =

      `⁠FALSE⁠`

    nrow.ncol =

      `⁠FALSE⁠`

    augmented =

      `⁠FALSE⁠`

    aug.factor =

      `⁠1⁠`

    aug.constr =

      `⁠NULL⁠`

    n.div.by =

      `⁠NULL⁠`

    n.required =

      `⁠FALSE⁠`

    set.default.values =

      `⁠FALSE⁠`

    pdf =

      `⁠clinear⁠`

  Number of hyperparmeters is 1.

  Hyperparameter 'theta'
    hyperid =

      `⁠37001⁠`

    name =

      `⁠beta⁠`

    short.name =

      `⁠b⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x, REPLACE.ME.low, REPLACE.ME.high) { if (all(is.infinite(c(low, high))) || low == high) { stopifnot(low < high) return(x) } else if (all(is.finite(c(low, high)))) { stopifnot(low < high) return(log(-(low - x) / (high - x))) } else if (is.finite(low) && is.infinite(high) && high > low) { return(log(x - low)) } else { stop("Condition not yet implemented") } }⁠`

    from.theta =

      `⁠function(x, REPLACE.ME.low, REPLACE.ME.high) { if (all(is.infinite(c(low, high))) || low == high) { stopifnot(low < high) return(x) } else if (all(is.finite(c(low, high)))) { stopifnot(low < high) return(low + exp(x) / (1 + exp(x)) * (high - low)) } else if (is.finite(low) && is.infinite(high) && high > low) { return(low + exp(x)) } else { stop("Condition not yet implemented") } }⁠`

Model 'sigm'.
  Properties:
    doc =

      `⁠Sigmoidal effect of a covariate⁠`

    constr =

      `⁠FALSE⁠`

    nrow.ncol =

      `⁠FALSE⁠`

    augmented =

      `⁠FALSE⁠`

    aug.factor =

      `⁠1⁠`

    aug.constr =

      `⁠NULL⁠`

    n.div.by =

      `⁠NULL⁠`

    n.required =

      `⁠FALSE⁠`

    set.default.values =

      `⁠FALSE⁠`

    pdf =

      `⁠sigm⁠`

  Number of hyperparmeters is 3.

  Hyperparameter 'theta1'
    hyperid =

      `⁠38001⁠`

    name =

      `⁠beta⁠`

    short.name =

      `⁠b⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠38002⁠`

    name =

      `⁠loghalflife⁠`

    short.name =

      `⁠halflife⁠`

    initial =

      `⁠3⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠3 1⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta3'
    hyperid =

      `⁠38003⁠`

    name =

      `⁠logshape⁠`

    short.name =

      `⁠shape⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠10 10⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

Model 'revsigm'.
  Properties:
    doc =

      `⁠Reverse sigmoidal effect of a covariate⁠`

    constr =

      `⁠FALSE⁠`

    nrow.ncol =

      `⁠FALSE⁠`

    augmented =

      `⁠FALSE⁠`

    aug.factor =

      `⁠1⁠`

    aug.constr =

      `⁠NULL⁠`

    n.div.by =

      `⁠NULL⁠`

    n.required =

      `⁠FALSE⁠`

    set.default.values =

      `⁠FALSE⁠`

    pdf =

      `⁠sigm⁠`

  Number of hyperparmeters is 3.

  Hyperparameter 'theta1'
    hyperid =

      `⁠39001⁠`

    name =

      `⁠beta⁠`

    short.name =

      `⁠b⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠39002⁠`

    name =

      `⁠loghalflife⁠`

    short.name =

      `⁠halflife⁠`

    initial =

      `⁠3⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠3 1⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta3'
    hyperid =

      `⁠39003⁠`

    name =

      `⁠logshape⁠`

    short.name =

      `⁠shape⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠10 10⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

Model 'log1exp'.
  Properties:
    doc =

      `⁠A nonlinear model of a covariate⁠`

    constr =

      `⁠FALSE⁠`

    nrow.ncol =

      `⁠FALSE⁠`

    augmented =

      `⁠FALSE⁠`

    aug.factor =

      `⁠1⁠`

    aug.constr =

      `⁠NULL⁠`

    n.div.by =

      `⁠NULL⁠`

    n.required =

      `⁠FALSE⁠`

    set.default.values =

      `⁠FALSE⁠`

    pdf =

      `⁠log1exp⁠`

  Number of hyperparmeters is 3.

  Hyperparameter 'theta1'
    hyperid =

      `⁠39011⁠`

    name =

      `⁠beta⁠`

    short.name =

      `⁠b⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 1⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠39012⁠`

    name =

      `⁠alpha⁠`

    short.name =

      `⁠a⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 1⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta3'
    hyperid =

      `⁠39013⁠`

    name =

      `⁠gamma⁠`

    short.name =

      `⁠g⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 1⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

Model 'logdist'.
  Properties:
    doc =

      `⁠A nonlinear model of a covariate⁠`

    constr =

      `⁠FALSE⁠`

    nrow.ncol =

      `⁠FALSE⁠`

    augmented =

      `⁠FALSE⁠`

    aug.factor =

      `⁠1⁠`

    aug.constr =

      `⁠NULL⁠`

    n.div.by =

      `⁠NULL⁠`

    n.required =

      `⁠FALSE⁠`

    set.default.values =

      `⁠FALSE⁠`

    pdf =

      `⁠logdist⁠`

  Number of hyperparmeters is 3.

  Hyperparameter 'theta1'
    hyperid =

      `⁠39021⁠`

    name =

      `⁠beta⁠`

    short.name =

      `⁠b⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 1⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠39022⁠`

    name =

      `⁠alpha1⁠`

    short.name =

      `⁠a1⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠0.1 1⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta3'
    hyperid =

      `⁠39023⁠`

    name =

      `⁠alpha2⁠`

    short.name =

      `⁠a2⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠0.1 1⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

### 'group'

Valid models in this section are:

Model 'exchangeable'.
  Properties:
    doc =

      `⁠Exchangeable correlations⁠`

  Number of hyperparmeters is 1.

  Hyperparameter 'theta'
    hyperid =

      `⁠40001⁠`

    name =

      `⁠logit correlation⁠`

    short.name =

      `⁠rho⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 0.2⁠`

    to.theta =

      `⁠function(x, REPLACE.ME.ngroup) log((1 + x * (ngroup - 1)) / (1 - x))⁠`

    from.theta =

      `⁠function(x, REPLACE.ME.ngroup) (exp(x) - 1) / (exp(x) + ngroup - 1)⁠`

Model 'exchangeablepos'.
  Properties:
    doc =

      `⁠Exchangeable positive correlations⁠`

  Number of hyperparmeters is 1.

  Hyperparameter 'theta'
    hyperid =

      `⁠40101⁠`

    name =

      `⁠logit correlation⁠`

    short.name =

      `⁠rho⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠pc.cor0⁠`

    param =

      `⁠0.5 0.5⁠`

    to.theta =

      `⁠function(x) log(x / (1 - x))⁠`

    from.theta =

      `⁠function(x) exp(x) / (1 + exp(x))⁠`

Model 'ar1'.
  Properties:
    doc =

      `⁠AR(1) correlations⁠`

  Number of hyperparmeters is 1.

  Hyperparameter 'theta'
    hyperid =

      `⁠41001⁠`

    name =

      `⁠logit correlation⁠`

    short.name =

      `⁠rho⁠`

    initial =

      `⁠2⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 0.15⁠`

    to.theta =

      `⁠function(x) log((1 + x) / (1 - x))⁠`

    from.theta =

      `⁠function(x) 2 * exp(x) / (1 + exp(x)) - 1⁠`

Model 'ar'.
  Properties:
    doc =

      `⁠AR(p) correlations⁠`

  Number of hyperparmeters is 11.

  Hyperparameter 'theta1'
    hyperid =

      `⁠42001⁠`

    name =

      `⁠log precision⁠`

    short.name =

      `⁠prec⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠TRUE⁠`

    prior =

      `⁠pc.prec⁠`

    param =

      `⁠3 0.01⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠42002⁠`

    name =

      `⁠pacf1⁠`

    short.name =

      `⁠pacf1⁠`

    initial =

      `⁠2⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠pc.cor0⁠`

    param =

      `⁠0.5 0.5⁠`

    to.theta =

      `⁠function(x) log((1 + x) / (1 - x))⁠`

    from.theta =

      `⁠function(x) 2 * exp(x) / (1 + exp(x)) - 1⁠`

  Hyperparameter 'theta3'
    hyperid =

      `⁠42003⁠`

    name =

      `⁠pacf2⁠`

    short.name =

      `⁠pacf2⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠pc.cor0⁠`

    param =

      `⁠0.5 0.4⁠`

    to.theta =

      `⁠function(x) log((1 + x) / (1 - x))⁠`

    from.theta =

      `⁠function(x) 2 * exp(x) / (1 + exp(x)) - 1⁠`

  Hyperparameter 'theta4'
    hyperid =

      `⁠42004⁠`

    name =

      `⁠pacf3⁠`

    short.name =

      `⁠pacf3⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠pc.cor0⁠`

    param =

      `⁠0.5 0.3⁠`

    to.theta =

      `⁠function(x) log((1 + x) / (1 - x))⁠`

    from.theta =

      `⁠function(x) 2 * exp(x) / (1 + exp(x)) - 1⁠`

  Hyperparameter 'theta5'
    hyperid =

      `⁠42005⁠`

    name =

      `⁠pacf4⁠`

    short.name =

      `⁠pacf4⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠pc.cor0⁠`

    param =

      `⁠0.5 0.2⁠`

    to.theta =

      `⁠function(x) log((1 + x) / (1 - x))⁠`

    from.theta =

      `⁠function(x) 2 * exp(x) / (1 + exp(x)) - 1⁠`

  Hyperparameter 'theta6'
    hyperid =

      `⁠42006⁠`

    name =

      `⁠pacf5⁠`

    short.name =

      `⁠pacf5⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠pc.cor0⁠`

    param =

      `⁠0.5 0.1⁠`

    to.theta =

      `⁠function(x) log((1 + x) / (1 - x))⁠`

    from.theta =

      `⁠function(x) 2 * exp(x) / (1 + exp(x)) - 1⁠`

  Hyperparameter 'theta7'
    hyperid =

      `⁠42007⁠`

    name =

      `⁠pacf6⁠`

    short.name =

      `⁠pacf6⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠pc.cor0⁠`

    param =

      `⁠0.5 0.1⁠`

    to.theta =

      `⁠function(x) log((1 + x) / (1 - x))⁠`

    from.theta =

      `⁠function(x) 2 * exp(x) / (1 + exp(x)) - 1⁠`

  Hyperparameter 'theta8'
    hyperid =

      `⁠42008⁠`

    name =

      `⁠pacf7⁠`

    short.name =

      `⁠pacf7⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠pc.cor0⁠`

    param =

      `⁠0.5 0.1⁠`

    to.theta =

      `⁠function(x) log((1 + x) / (1 - x))⁠`

    from.theta =

      `⁠function(x) 2 * exp(x) / (1 + exp(x)) - 1⁠`

  Hyperparameter 'theta9'
    hyperid =

      `⁠42009⁠`

    name =

      `⁠pacf8⁠`

    short.name =

      `⁠pacf8⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠pc.cor0⁠`

    param =

      `⁠0.5 0.1⁠`

    to.theta =

      `⁠function(x) log((1 + x) / (1 - x))⁠`

    from.theta =

      `⁠function(x) 2 * exp(x) / (1 + exp(x)) - 1⁠`

  Hyperparameter 'theta10'
    hyperid =

      `⁠42010⁠`

    name =

      `⁠pacf9⁠`

    short.name =

      `⁠pacf9⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠pc.cor0⁠`

    param =

      `⁠0.5 0.1⁠`

    to.theta =

      `⁠function(x) log((1 + x) / (1 - x))⁠`

    from.theta =

      `⁠function(x) 2 * exp(x) / (1 + exp(x)) - 1⁠`

  Hyperparameter 'theta11'
    hyperid =

      `⁠42011⁠`

    name =

      `⁠pacf10⁠`

    short.name =

      `⁠pacf10⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠pc.cor0⁠`

    param =

      `⁠0.5 0.1⁠`

    to.theta =

      `⁠function(x) log((1 + x) / (1 - x))⁠`

    from.theta =

      `⁠function(x) 2 * exp(x) / (1 + exp(x)) - 1⁠`

Model 'rw1'.
  Properties:
    doc =

      `⁠Random walk of order 1⁠`

  Number of hyperparmeters is 1.

  Hyperparameter 'theta'
    hyperid =

      `⁠43001⁠`

    name =

      `⁠log precision⁠`

    short.name =

      `⁠prec⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 5e-05⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠TRUE⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

Model 'rw2'.
  Properties:
    doc =

      `⁠Random walk of order 2⁠`

  Number of hyperparmeters is 1.

  Hyperparameter 'theta'
    hyperid =

      `⁠44001⁠`

    name =

      `⁠log precision⁠`

    short.name =

      `⁠prec⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 5e-05⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠TRUE⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

Model 'besag'.
  Properties:
    doc =

      `⁠Besag model⁠`

  Number of hyperparmeters is 1.

  Hyperparameter 'theta'
    hyperid =

      `⁠45001⁠`

    name =

      `⁠log precision⁠`

    short.name =

      `⁠prec⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 5e-05⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠TRUE⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

Model 'iid'.
  Properties:
    doc =

      `⁠Independent model⁠`

  Number of hyperparmeters is 1.

  Hyperparameter 'theta'
    hyperid =

      `⁠46001⁠`

    name =

      `⁠log precision⁠`

    short.name =

      `⁠prec⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 5e-05⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠TRUE⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

### 'scopy'

Valid models in this section are:

Model 'rw1'.
  Properties:
    doc =

      `⁠Random walk of order 1⁠`

  Number of hyperparmeters is 0.

Model 'rw2'.
  Properties:
    doc =

      `⁠Random walk of order 2⁠`

  Number of hyperparmeters is 0.

### 'mix'

Valid models in this section are:

Model 'gaussian'.
  Properties:
    doc =

      `⁠Gaussian mixture⁠`

  Number of hyperparmeters is 1.

  Hyperparameter 'theta'
    hyperid =

      `⁠47001⁠`

    name =

      `⁠log precision⁠`

    short.name =

      `⁠prec⁠`

    output.name =

      `⁠Precision for the Gaussian observations⁠`

    output.name.intern =

      `⁠Log precision for the Gaussian observations⁠`

    prior =

      `⁠pc.prec⁠`

    param =

      `⁠1 0.01⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

Model 'loggamma'.
  Properties:
    doc =

      `⁠LogGamma mixture⁠`

  Number of hyperparmeters is 1.

  Hyperparameter 'theta'
    hyperid =

      `⁠47101⁠`

    name =

      `⁠log precision⁠`

    short.name =

      `⁠prec⁠`

    prior =

      `⁠pc.mgamma⁠`

    param =

      `⁠4.8⁠`

    initial =

      `⁠4⁠`

    fixed =

      `⁠FALSE⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

Model 'mloggamma'.
  Properties:
    doc =

      `⁠Minus-LogGamma mixture⁠`

  Number of hyperparmeters is 1.

  Hyperparameter 'theta'
    hyperid =

      `⁠47201⁠`

    name =

      `⁠log precision⁠`

    short.name =

      `⁠prec⁠`

    prior =

      `⁠pc.mgamma⁠`

    param =

      `⁠4.8⁠`

    initial =

      `⁠4⁠`

    fixed =

      `⁠FALSE⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

### 'link'

Valid models in this section are:

Model 'default'.
  Properties:
    doc =

      `⁠The default link⁠`

  Number of hyperparmeters is 0.

Model 'cloglog'.
  Properties:
    doc =

      `⁠The complementary log-log link⁠`

  Number of hyperparmeters is 0.

Model 'ccloglog'.
  Properties:
    doc =

      `⁠The complement complementary log-log link⁠`

  Number of hyperparmeters is 0.

Model 'loglog'.
  Properties:
    doc =

      `⁠The log-log link⁠`

  Number of hyperparmeters is 0.

Model 'identity'.
  Properties:
    doc =

      `⁠The identity link⁠`

  Number of hyperparmeters is 0.

Model 'inverse'.
  Properties:
    doc =

      `⁠The inverse link⁠`

  Number of hyperparmeters is 0.

Model 'log'.
  Properties:
    doc =

      `⁠The log-link⁠`

  Number of hyperparmeters is 0.

Model 'loga'.
  Properties:
    doc =

      `⁠The loga-link⁠`

  Number of hyperparmeters is 0.

Model 'neglog'.
  Properties:
    doc =

      `⁠The negative log-link⁠`

  Number of hyperparmeters is 0.

Model 'logit'.
  Properties:
    doc =

      `⁠The logit-link⁠`

  Number of hyperparmeters is 0.

Model 'probit'.
  Properties:
    doc =

      `⁠The probit-link⁠`

  Number of hyperparmeters is 0.

Model 'cauchit'.
  Properties:
    doc =

      `⁠The cauchit-link⁠`

  Number of hyperparmeters is 0.

Model 'tan'.
  Properties:
    doc =

      `⁠The tan-link⁠`

    pdf =

      `⁠circular⁠`

  Number of hyperparmeters is 0.

Model 'tanpi'.
  Properties:
    doc =

      `⁠The tanpi-link⁠`

    pdf =

      `⁠circular⁠`

  Number of hyperparmeters is 0.

Model 'quantile'.
  Properties:
    doc =

      `⁠The quantile-link⁠`

  Number of hyperparmeters is 0.

Model 'pquantile'.
  Properties:
    doc =

      `⁠The population quantile-link⁠`

  Number of hyperparmeters is 0.

Model 'sslogit'.
  Properties:
    doc =

      `⁠Logit link with sensitivity and specificity⁠`

    status =

      `⁠disabled⁠`

    pdf =

      `⁠NA⁠`

  Number of hyperparmeters is 2.

  Hyperparameter 'theta1'
    hyperid =

      `⁠48001⁠`

    name =

      `⁠sensitivity⁠`

    short.name =

      `⁠sens⁠`

    prior =

      `⁠logitbeta⁠`

    param =

      `⁠10 5⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    to.theta =

      `⁠function(x) log(x / (1 - x))⁠`

    from.theta =

      `⁠function(x) exp(x) / (1 + exp(x))⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠48002⁠`

    name =

      `⁠specificity⁠`

    short.name =

      `⁠spec⁠`

    prior =

      `⁠logitbeta⁠`

    param =

      `⁠10 5⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    to.theta =

      `⁠function(x) log(x / (1 - x))⁠`

    from.theta =

      `⁠function(x) exp(x) / (1 + exp(x))⁠`

Model 'logoffset'.
  Properties:
    doc =

      `⁠Log-link with an offset⁠`

    pdf =

      `⁠logoffset⁠`

  Number of hyperparmeters is 1.

  Hyperparameter 'theta'
    hyperid =

      `⁠49001⁠`

    name =

      `⁠beta⁠`

    short.name =

      `⁠b⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠TRUE⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

Model 'logitoffset'.
  Properties:
    doc =

      `⁠Logit-link with an offset⁠`

    pdf =

      `⁠logitoffset⁠`

  Number of hyperparmeters is 1.

  Hyperparameter 'theta'
    hyperid =

      `⁠49011⁠`

    name =

      `⁠prob⁠`

    short.name =

      `⁠p⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠-1 100⁠`

    initial =

      `⁠-1⁠`

    fixed =

      `⁠FALSE⁠`

    to.theta =

      `⁠function(x) log(x / (1 - x))⁠`

    from.theta =

      `⁠function(x) exp(x) / (1 + exp(x))⁠`

Model 'robit'.
  Properties:
    doc =

      `⁠Robit link⁠`

    pdf =

      `⁠robit⁠`

  Number of hyperparmeters is 1.

  Hyperparameter 'theta'
    hyperid =

      `⁠49021⁠`

    name =

      `⁠log degrees of freedom⁠`

    short.name =

      `⁠dof⁠`

    initial =

      `⁠1.6094379124341⁠`

    fixed =

      `⁠TRUE⁠`

    prior =

      `⁠pc.dof⁠`

    param =

      `⁠50 0.5⁠`

    to.theta =

      `⁠function(x) log(x - 2)⁠`

    from.theta =

      `⁠function(x) 2 + exp(x)⁠`

Model 'sn'.
  Properties:
    doc =

      `⁠Skew-normal link⁠`

    pdf =

      `⁠linksn⁠`

  Number of hyperparmeters is 2.

  Hyperparameter 'theta1'
    hyperid =

      `⁠49031⁠`

    name =

      `⁠skewness⁠`

    short.name =

      `⁠skew⁠`

    initial =

      `⁠0.00123456789⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠pc.sn⁠`

    param =

      `⁠10⁠`

    to.theta =

      `⁠function(x, skew.max = 0.988) log((1 + x / skew.max) / (1 - x / skew.max))⁠`

    from.theta =

      `⁠function(x, skew.max = 0.988) skew.max * (2 * exp(x) / (1 + exp(x)) - 1)⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠49032⁠`

    name =

      `⁠intercept⁠`

    short.name =

      `⁠p0⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠linksnintercept⁠`

    param =

      `⁠0 0⁠`

    to.theta =

      `⁠function(x) log(x / (1 - x))⁠`

    from.theta =

      `⁠function(x) exp(x) / (1 + exp(x))⁠`

Model 'gevit'.
  Properties:
    doc =

      `⁠GEVIT link⁠`

    pdf =

      `⁠gevit⁠`

  Number of hyperparmeters is 2.

  Hyperparameter 'theta1'
    hyperid =

      `⁠49033⁠`

    name =

      `⁠gev tail⁠`

    short.name =

      `⁠tail⁠`

    initial =

      `⁠0.1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠pc.egptail⁠`

    param =

      `⁠5 -0.5 0.5⁠`

    to.theta =

      `⁠function(x, interval = c(REPLACE.ME.low, REPLACE.ME.high)) log(-(interval[1] - x) / (interval[2] - x))⁠`

    from.theta =

      `⁠function(x, interval = c(REPLACE.ME.low, REPLACE.ME.high)) interval[1] + (interval[2] - interval[1]) * exp(x) / (1.0 + exp(x))⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠49034⁠`

    name =

      `⁠gev p0⁠`

    short.name =

      `⁠p0⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 1⁠`

    to.theta =

      `⁠function(x) log(x / (1 - x))⁠`

    from.theta =

      `⁠function(x) 1 / (1 + exp(-x))⁠`

Model 'cgevit'.
  Properties:
    doc =

      `⁠Complement GEVIT link⁠`

    pdf =

      `⁠gevit⁠`

  Number of hyperparmeters is 2.

  Hyperparameter 'theta1'
    hyperid =

      `⁠49035⁠`

    name =

      `⁠gev tail⁠`

    short.name =

      `⁠tail⁠`

    initial =

      `⁠-3⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠pc.gevtail⁠`

    param =

      `⁠7 0 0.5⁠`

    to.theta =

      `⁠function(x, interval = c(REPLACE.ME.low, REPLACE.ME.high)) log(-(interval[1] - x) / (interval[2] - x))⁠`

    from.theta =

      `⁠function(x, interval = c(REPLACE.ME.low, REPLACE.ME.high)) interval[1] + (interval[2] - interval[1]) * exp(x) / (1.0 + exp(x))⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠49036⁠`

    name =

      `⁠gev p0⁠`

    short.name =

      `⁠p0⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 1⁠`

    to.theta =

      `⁠function(x) log(x / (1 - x))⁠`

    from.theta =

      `⁠function(x) 1 / (1 + exp(-x))⁠`

Model 'powerlogit'.
  Properties:
    doc =

      `⁠Power logit link⁠`

    pdf =

      `⁠powerlogit⁠`

  Number of hyperparmeters is 2.

  Hyperparameter 'theta1'
    hyperid =

      `⁠49131⁠`

    name =

      `⁠power⁠`

    short.name =

      `⁠power⁠`

    initial =

      `⁠0.00123456789⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠49132⁠`

    name =

      `⁠intercept⁠`

    short.name =

      `⁠p0⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠logitbeta⁠`

    param =

      `⁠1 1⁠`

    to.theta =

      `⁠function(x) log(x / (1 - x))⁠`

    from.theta =

      `⁠function(x) exp(x) / (1 + exp(x))⁠`

Model 'test1'.
  Properties:
    doc =

      `⁠A test1-link function (experimental)⁠`

    pdf =

      `⁠NA⁠`

  Number of hyperparmeters is 1.

  Hyperparameter 'theta'
    hyperid =

      `⁠50001⁠`

    name =

      `⁠beta⁠`

    short.name =

      `⁠b⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

Model 'special1'.
  Properties:
    doc =

      `⁠A special1-link function (experimental)⁠`

    pdf =

      `⁠NA⁠`

  Number of hyperparmeters is 11.

  Hyperparameter 'theta1'
    hyperid =

      `⁠51001⁠`

    name =

      `⁠log precision⁠`

    short.name =

      `⁠prec⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 1⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠51002⁠`

    name =

      `⁠beta1⁠`

    short.name =

      `⁠beta1⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠mvnorm⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta3'
    hyperid =

      `⁠51003⁠`

    name =

      `⁠beta2⁠`

    short.name =

      `⁠beta2⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta4'
    hyperid =

      `⁠51004⁠`

    name =

      `⁠beta3⁠`

    short.name =

      `⁠beta3⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta5'
    hyperid =

      `⁠51005⁠`

    name =

      `⁠beta4⁠`

    short.name =

      `⁠beta4⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta6'
    hyperid =

      `⁠51006⁠`

    name =

      `⁠beta5⁠`

    short.name =

      `⁠beta5⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta7'
    hyperid =

      `⁠51007⁠`

    name =

      `⁠beta6⁠`

    short.name =

      `⁠beta6⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta8'
    hyperid =

      `⁠51008⁠`

    name =

      `⁠beta7⁠`

    short.name =

      `⁠beta7⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta9'
    hyperid =

      `⁠51009⁠`

    name =

      `⁠beta8⁠`

    short.name =

      `⁠beta8⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta10'
    hyperid =

      `⁠51010⁠`

    name =

      `⁠beta9⁠`

    short.name =

      `⁠beta9⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta11'
    hyperid =

      `⁠51011⁠`

    name =

      `⁠beta10⁠`

    short.name =

      `⁠beta10⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

Model 'special2'.
  Properties:
    doc =

      `⁠A special2-link function (experimental)⁠`

    pdf =

      `⁠NA⁠`

  Number of hyperparmeters is 1.

  Hyperparameter 'theta'
    hyperid =

      `⁠52001⁠`

    name =

      `⁠beta⁠`

    short.name =

      `⁠b⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

### 'predictor'

Valid models in this section are:

Model 'predictor'.
  Properties:
    doc =

      `⁠(do not use)⁠`

  Number of hyperparmeters is 1.

  Hyperparameter 'theta'
    hyperid =

      `⁠53001⁠`

    name =

      `⁠log precision⁠`

    short.name =

      `⁠prec⁠`

    initial =

      `⁠13.8155105579643⁠`

    fixed =

      `⁠TRUE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 1e-05⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

### 'hazard'

Valid models in this section are:

Model 'rw1'.
  Properties:
    doc =

      `⁠A random walk of order 1 for the log-hazard⁠`

  Number of hyperparmeters is 1.

  Hyperparameter 'theta'
    hyperid =

      `⁠54001⁠`

    name =

      `⁠log precision⁠`

    short.name =

      `⁠prec⁠`

    initial =

      `⁠4⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 5e-05⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

Model 'rw2'.
  Properties:
    doc =

      `⁠A random walk of order 2 for the log-hazard⁠`

  Number of hyperparmeters is 1.

  Hyperparameter 'theta'
    hyperid =

      `⁠55001⁠`

    name =

      `⁠log precision⁠`

    short.name =

      `⁠prec⁠`

    initial =

      `⁠4⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 5e-05⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

Model 'iid'.
  Properties:
    doc =

      `⁠An iid model for the log-hazard⁠`

  Number of hyperparmeters is 1.

  Hyperparameter 'theta'
    hyperid =

      `⁠55501⁠`

    name =

      `⁠log precision⁠`

    short.name =

      `⁠prec⁠`

    initial =

      `⁠4⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 5e-05⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

### 'likelihood'

Valid models in this section are:

Model 'fl'.
  Properties:
    doc =

      `⁠The fl likelihood⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠TRUE⁠`

    link =

      `⁠default identity⁠`

    pdf =

      `⁠fl⁠`

  Number of hyperparmeters is 0.

Model 'poisson'.
  Properties:
    doc =

      `⁠The Poisson likelihood⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠TRUE⁠`

    link =

      `⁠default log logoffset quantile test1 special1 special2⁠`

    pdf =

      `⁠poisson⁠`

  Number of hyperparmeters is 0.

Model 'npoisson'.
  Properties:
    doc =

      `⁠The Normal approximation to the Poisson likelihood⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠TRUE⁠`

    link =

      `⁠default log logoffset⁠`

    pdf =

      `⁠poisson⁠`

  Number of hyperparmeters is 0.

Model 'nzpoisson'.
  Properties:
    doc =

      `⁠The nzPoisson likelihood⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠TRUE⁠`

    link =

      `⁠default log logoffset⁠`

    pdf =

      `⁠nzpoisson⁠`

  Number of hyperparmeters is 0.

Model 'xpoisson'.
  Properties:
    doc =

      `⁠The Poisson likelihood (expert version)⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠TRUE⁠`

    link =

      `⁠default log logoffset quantile test1 special1 special2⁠`

    pdf =

      `⁠poisson⁠`

  Number of hyperparmeters is 0.

Model 'cenpoisson'.
  Properties:
    doc =

      `⁠Then censored Poisson likelihood⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠TRUE⁠`

    link =

      `⁠default log logoffset test1 special1 special2⁠`

    pdf =

      `⁠cenpoisson⁠`

  Number of hyperparmeters is 0.

Model 'cenpoisson2'.
  Properties:
    doc =

      `⁠Then censored Poisson likelihood (version 2)⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠TRUE⁠`

    link =

      `⁠default log logoffset test1 special1 special2⁠`

    pdf =

      `⁠cenpoisson2⁠`

  Number of hyperparmeters is 0.

Model 'gpoisson'.
  Properties:
    doc =

      `⁠The generalized Poisson likelihood⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠TRUE⁠`

    link =

      `⁠default log logoffset⁠`

    pdf =

      `⁠gpoisson⁠`

  Number of hyperparmeters is 2.

  Hyperparameter 'theta1'
    hyperid =

      `⁠56001⁠`

    name =

      `⁠overdispersion⁠`

    short.name =

      `⁠phi⁠`

    output.name =

      `⁠Overdispersion for gpoisson⁠`

    output.name.intern =

      `⁠Log overdispersion for gpoisson⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 1⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠56002⁠`

    name =

      `⁠p⁠`

    short.name =

      `⁠p⁠`

    output.name =

      `⁠Parameter p for gpoisson⁠`

    output.name.intern =

      `⁠Parameter p_intern for gpoisson⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠TRUE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

Model 'poisson.special1'.
  Properties:
    doc =

      `⁠The Poisson.special1 likelihood⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠TRUE⁠`

    link =

      `⁠default log⁠`

    pdf =

      `⁠poisson-special⁠`

  Number of hyperparmeters is 1.

  Hyperparameter 'theta'
    hyperid =

      `⁠56100⁠`

    name =

      `⁠logit probability⁠`

    short.name =

      `⁠prob⁠`

    output.name =

      `⁠one-probability parameter for poisson.special1⁠`

    output.name.intern =

      `⁠intern one-probability parameter for poisson.special1⁠`

    initial =

      `⁠-1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠gaussian⁠`

    param =

      `⁠-1 0.2⁠`

    to.theta =

      `⁠function(x) log(x / (1 - x))⁠`

    from.theta =

      `⁠function(x) exp(x) / (1 + exp(x))⁠`

Model '0poisson'.
  Properties:
    doc =

      `⁠New 0-inflated Poisson⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠TRUE⁠`

    link =

      `⁠default log quantile⁠`

    link.simple =

      `⁠default logit cauchit probit cloglog ccloglog⁠`

    pdf =

      `⁠0inflated⁠`

  Number of hyperparmeters is 10.

  Hyperparameter 'theta1'
    hyperid =

      `⁠56201⁠`

    name =

      `⁠beta1⁠`

    short.name =

      `⁠beta1⁠`

    output.name =

      `⁠beta1 for 0poisson observations⁠`

    output.name.intern =

      `⁠beta1 for 0poisson observations⁠`

    initial =

      `⁠-4⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠-4 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠56202⁠`

    name =

      `⁠beta2⁠`

    short.name =

      `⁠beta2⁠`

    output.name =

      `⁠beta2 for 0poisson observations⁠`

    output.name.intern =

      `⁠beta2 for 0poisson observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta3'
    hyperid =

      `⁠56203⁠`

    name =

      `⁠beta3⁠`

    short.name =

      `⁠beta3⁠`

    output.name =

      `⁠beta3 for 0poisson observations⁠`

    output.name.intern =

      `⁠beta3 for 0poisson observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta4'
    hyperid =

      `⁠56204⁠`

    name =

      `⁠beta4⁠`

    short.name =

      `⁠beta4⁠`

    output.name =

      `⁠beta4 for 0poisson observations⁠`

    output.name.intern =

      `⁠beta4 for 0poisson observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta5'
    hyperid =

      `⁠56205⁠`

    name =

      `⁠beta5⁠`

    short.name =

      `⁠beta5⁠`

    output.name =

      `⁠beta5 for 0poisson observations⁠`

    output.name.intern =

      `⁠beta5 for 0poisson observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta6'
    hyperid =

      `⁠56206⁠`

    name =

      `⁠beta6⁠`

    short.name =

      `⁠beta6⁠`

    output.name =

      `⁠beta6 for 0poisson observations⁠`

    output.name.intern =

      `⁠beta6 for 0poisson observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta7'
    hyperid =

      `⁠56207⁠`

    name =

      `⁠beta7⁠`

    short.name =

      `⁠beta7⁠`

    output.name =

      `⁠beta7 for 0poisson observations⁠`

    output.name.intern =

      `⁠beta7 for 0poisson observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta8'
    hyperid =

      `⁠56208⁠`

    name =

      `⁠beta8⁠`

    short.name =

      `⁠beta8⁠`

    output.name =

      `⁠beta8 for 0poisson observations⁠`

    output.name.intern =

      `⁠beta8 for 0poisson observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta9'
    hyperid =

      `⁠56209⁠`

    name =

      `⁠beta9⁠`

    short.name =

      `⁠beta9⁠`

    output.name =

      `⁠beta9 for 0poisson observations⁠`

    output.name.intern =

      `⁠beta9 for 0poisson observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta10'
    hyperid =

      `⁠56210⁠`

    name =

      `⁠beta10⁠`

    short.name =

      `⁠beta10⁠`

    output.name =

      `⁠beta10 for 0poisson observations⁠`

    output.name.intern =

      `⁠beta10 for 0poisson observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

Model '0poissonS'.
  Properties:
    doc =

      `⁠New 0-inflated Poisson Swap⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠TRUE⁠`

    link =

      `⁠default logit loga cauchit probit cloglog ccloglog loglog log sslogit logitoffset quantile pquantile robit sn powerlogit⁠`

    link.simple =

      `⁠default log⁠`

    pdf =

      `⁠0inflated⁠`

  Number of hyperparmeters is 10.

  Hyperparameter 'theta1'
    hyperid =

      `⁠56301⁠`

    name =

      `⁠beta1⁠`

    short.name =

      `⁠beta1⁠`

    output.name =

      `⁠beta1 for 0poissonS observations⁠`

    output.name.intern =

      `⁠beta1 for 0poissonS observations⁠`

    initial =

      `⁠-4⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠-4 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠56302⁠`

    name =

      `⁠beta2⁠`

    short.name =

      `⁠beta2⁠`

    output.name =

      `⁠beta2 for 0poissonS observations⁠`

    output.name.intern =

      `⁠beta2 for 0poissonS observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta3'
    hyperid =

      `⁠56303⁠`

    name =

      `⁠beta3⁠`

    short.name =

      `⁠beta3⁠`

    output.name =

      `⁠beta3 for 0poissonS observations⁠`

    output.name.intern =

      `⁠beta3 for 0poissonS observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta4'
    hyperid =

      `⁠56304⁠`

    name =

      `⁠beta4⁠`

    short.name =

      `⁠beta4⁠`

    output.name =

      `⁠beta4 for 0poissonS observations⁠`

    output.name.intern =

      `⁠beta4 for 0poissonS observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta5'
    hyperid =

      `⁠56305⁠`

    name =

      `⁠beta5⁠`

    short.name =

      `⁠beta5⁠`

    output.name =

      `⁠beta5 for 0poissonS observations⁠`

    output.name.intern =

      `⁠beta5 for 0poissonS observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta6'
    hyperid =

      `⁠56306⁠`

    name =

      `⁠beta6⁠`

    short.name =

      `⁠beta6⁠`

    output.name =

      `⁠beta6 for 0poissonS observations⁠`

    output.name.intern =

      `⁠beta6 for 0poissonS observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta7'
    hyperid =

      `⁠56307⁠`

    name =

      `⁠beta7⁠`

    short.name =

      `⁠beta7⁠`

    output.name =

      `⁠beta7 for 0poissonS observations⁠`

    output.name.intern =

      `⁠beta7 for 0poissonS observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta8'
    hyperid =

      `⁠56308⁠`

    name =

      `⁠beta8⁠`

    short.name =

      `⁠beta8⁠`

    output.name =

      `⁠beta8 for 0poissonS observations⁠`

    output.name.intern =

      `⁠beta8 for 0poissonS observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta9'
    hyperid =

      `⁠56309⁠`

    name =

      `⁠beta9⁠`

    short.name =

      `⁠beta9⁠`

    output.name =

      `⁠beta9 for 0poissonS observations⁠`

    output.name.intern =

      `⁠beta9 for 0poissonS observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta10'
    hyperid =

      `⁠56310⁠`

    name =

      `⁠beta10⁠`

    short.name =

      `⁠beta10⁠`

    output.name =

      `⁠beta10 for 0poissonS observations⁠`

    output.name.intern =

      `⁠beta10 for 0poissonS observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

Model '1poisson'.
  Properties:
    doc =

      `⁠New 1-inflated Poisson⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠TRUE⁠`

    link =

      `⁠default log quantile⁠`

    link.simple =

      `⁠default logit cauchit probit cloglog ccloglog⁠`

    pdf =

      `⁠0inflated⁠`

  Number of hyperparmeters is 10.

  Hyperparameter 'theta1'
    hyperid =

      `⁠56401⁠`

    name =

      `⁠beta1⁠`

    short.name =

      `⁠beta1⁠`

    output.name =

      `⁠beta1 for 1poisson observations⁠`

    output.name.intern =

      `⁠beta1 for 1poisson observations⁠`

    initial =

      `⁠-4⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠-4 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠56402⁠`

    name =

      `⁠beta2⁠`

    short.name =

      `⁠beta2⁠`

    output.name =

      `⁠beta2 for 1poisson observations⁠`

    output.name.intern =

      `⁠beta2 for 1poisson observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta3'
    hyperid =

      `⁠56403⁠`

    name =

      `⁠beta3⁠`

    short.name =

      `⁠beta3⁠`

    output.name =

      `⁠beta3 for 1poisson observations⁠`

    output.name.intern =

      `⁠beta3 for 1poisson observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta4'
    hyperid =

      `⁠56404⁠`

    name =

      `⁠beta4⁠`

    short.name =

      `⁠beta4⁠`

    output.name =

      `⁠beta4 for 1poisson observations⁠`

    output.name.intern =

      `⁠beta4 for 1poisson observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta5'
    hyperid =

      `⁠56405⁠`

    name =

      `⁠beta5⁠`

    short.name =

      `⁠beta5⁠`

    output.name =

      `⁠beta5 for 1poisson observations⁠`

    output.name.intern =

      `⁠beta5 for 1poisson observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta6'
    hyperid =

      `⁠56406⁠`

    name =

      `⁠beta6⁠`

    short.name =

      `⁠beta6⁠`

    output.name =

      `⁠beta6 for 1poisson observations⁠`

    output.name.intern =

      `⁠beta6 for 1poisson observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta7'
    hyperid =

      `⁠56407⁠`

    name =

      `⁠beta7⁠`

    short.name =

      `⁠beta7⁠`

    output.name =

      `⁠beta7 for 1poisson observations⁠`

    output.name.intern =

      `⁠beta7 for 1poisson observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta8'
    hyperid =

      `⁠56408⁠`

    name =

      `⁠beta8⁠`

    short.name =

      `⁠beta8⁠`

    output.name =

      `⁠beta8 for 1poisson observations⁠`

    output.name.intern =

      `⁠beta8 for 1poisson observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta9'
    hyperid =

      `⁠56409⁠`

    name =

      `⁠beta9⁠`

    short.name =

      `⁠beta9⁠`

    output.name =

      `⁠beta9 for 1poisson observations⁠`

    output.name.intern =

      `⁠beta9 for 1poisson observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta10'
    hyperid =

      `⁠56410⁠`

    name =

      `⁠beta10⁠`

    short.name =

      `⁠beta10⁠`

    output.name =

      `⁠beta10 for 1poisson observations⁠`

    output.name.intern =

      `⁠beta10 for 1poisson observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

Model '1poissonS'.
  Properties:
    doc =

      `⁠New 1-inflated Poisson Swap⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠TRUE⁠`

    link =

      `⁠default logit loga cauchit probit cloglog ccloglog loglog log sslogit logitoffset quantile pquantile robit sn powerlogit⁠`

    link.simple =

      `⁠default log⁠`

    pdf =

      `⁠0inflated⁠`

  Number of hyperparmeters is 10.

  Hyperparameter 'theta1'
    hyperid =

      `⁠56501⁠`

    name =

      `⁠beta1⁠`

    short.name =

      `⁠beta1⁠`

    output.name =

      `⁠beta1 for 1poissonS observations⁠`

    output.name.intern =

      `⁠beta1 for 1poissonS observations⁠`

    initial =

      `⁠-4⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠-4 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠56502⁠`

    name =

      `⁠beta2⁠`

    short.name =

      `⁠beta2⁠`

    output.name =

      `⁠beta2 for 1poissonS observations⁠`

    output.name.intern =

      `⁠beta2 for 1poissonS observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta3'
    hyperid =

      `⁠56503⁠`

    name =

      `⁠beta3⁠`

    short.name =

      `⁠beta3⁠`

    output.name =

      `⁠beta3 for 1poissonS observations⁠`

    output.name.intern =

      `⁠beta3 for 1poissonS observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta4'
    hyperid =

      `⁠56504⁠`

    name =

      `⁠beta4⁠`

    short.name =

      `⁠beta4⁠`

    output.name =

      `⁠beta4 for 1poissonS observations⁠`

    output.name.intern =

      `⁠beta4 for 1poissonS observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta5'
    hyperid =

      `⁠56505⁠`

    name =

      `⁠beta5⁠`

    short.name =

      `⁠beta5⁠`

    output.name =

      `⁠beta5 for 1poissonS observations⁠`

    output.name.intern =

      `⁠beta5 for 1poissonS observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta6'
    hyperid =

      `⁠56506⁠`

    name =

      `⁠beta6⁠`

    short.name =

      `⁠beta6⁠`

    output.name =

      `⁠beta6 for 1poissonS observations⁠`

    output.name.intern =

      `⁠beta6 for 1poissonS observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta7'
    hyperid =

      `⁠56507⁠`

    name =

      `⁠beta7⁠`

    short.name =

      `⁠beta7⁠`

    output.name =

      `⁠beta7 for 1poissonS observations⁠`

    output.name.intern =

      `⁠beta7 for 1poissonS observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta8'
    hyperid =

      `⁠56508⁠`

    name =

      `⁠beta8⁠`

    short.name =

      `⁠beta8⁠`

    output.name =

      `⁠beta8 for 1poissonS observations⁠`

    output.name.intern =

      `⁠beta8 for 1poissonS observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta9'
    hyperid =

      `⁠56509⁠`

    name =

      `⁠beta9⁠`

    short.name =

      `⁠beta9⁠`

    output.name =

      `⁠beta9 for 1poissonS observations⁠`

    output.name.intern =

      `⁠beta9 for 1poissonS observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta10'
    hyperid =

      `⁠56510⁠`

    name =

      `⁠beta10⁠`

    short.name =

      `⁠beta10⁠`

    output.name =

      `⁠beta10 for 1poissonS observations⁠`

    output.name.intern =

      `⁠beta10 for 1poissonS observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

Model 'bell'.
  Properties:
    doc =

      `⁠The Bell likelihood⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠TRUE⁠`

    link =

      `⁠default log⁠`

    pdf =

      `⁠bell⁠`

  Number of hyperparmeters is 0.

Model '0binomial'.
  Properties:
    doc =

      `⁠New 0-inflated Binomial⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠TRUE⁠`

    link =

      `⁠default logit loga cauchit probit cloglog ccloglog loglog log⁠`

    link.simple =

      `⁠default logit cauchit probit cloglog ccloglog⁠`

    pdf =

      `⁠0inflated⁠`

  Number of hyperparmeters is 10.

  Hyperparameter 'theta1'
    hyperid =

      `⁠56401⁠`

    name =

      `⁠beta1⁠`

    short.name =

      `⁠beta1⁠`

    output.name =

      `⁠beta1 for 0binomial observations⁠`

    output.name.intern =

      `⁠beta1 for 0binomial observations⁠`

    initial =

      `⁠-4⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠-4 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠56402⁠`

    name =

      `⁠beta2⁠`

    short.name =

      `⁠beta2⁠`

    output.name =

      `⁠beta2 for 0binomial observations⁠`

    output.name.intern =

      `⁠beta2 for 0binomial observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta3'
    hyperid =

      `⁠56403⁠`

    name =

      `⁠beta3⁠`

    short.name =

      `⁠beta3⁠`

    output.name =

      `⁠beta3 for 0binomial observations⁠`

    output.name.intern =

      `⁠beta3 for 0binomial observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta4'
    hyperid =

      `⁠56404⁠`

    name =

      `⁠beta4⁠`

    short.name =

      `⁠beta4⁠`

    output.name =

      `⁠beta4 for 0binomial observations⁠`

    output.name.intern =

      `⁠beta4 for 0binomial observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta5'
    hyperid =

      `⁠56405⁠`

    name =

      `⁠beta5⁠`

    short.name =

      `⁠beta5⁠`

    output.name =

      `⁠beta5 for 0binomial observations⁠`

    output.name.intern =

      `⁠beta5 for 0binomial observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta6'
    hyperid =

      `⁠56406⁠`

    name =

      `⁠beta6⁠`

    short.name =

      `⁠beta6⁠`

    output.name =

      `⁠beta6 for 0binomial observations⁠`

    output.name.intern =

      `⁠beta6 for 0binomial observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta7'
    hyperid =

      `⁠56407⁠`

    name =

      `⁠beta7⁠`

    short.name =

      `⁠beta7⁠`

    output.name =

      `⁠beta7 for 0binomial observations⁠`

    output.name.intern =

      `⁠beta7 for 0binomial observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta8'
    hyperid =

      `⁠56408⁠`

    name =

      `⁠beta8⁠`

    short.name =

      `⁠beta8⁠`

    output.name =

      `⁠beta8 for 0binomial observations⁠`

    output.name.intern =

      `⁠beta8 for 0binomial observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta9'
    hyperid =

      `⁠56409⁠`

    name =

      `⁠beta9⁠`

    short.name =

      `⁠beta9⁠`

    output.name =

      `⁠beta9 for 0binomial observations⁠`

    output.name.intern =

      `⁠beta9 for 0binomial observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta10'
    hyperid =

      `⁠56410⁠`

    name =

      `⁠beta10⁠`

    short.name =

      `⁠beta10⁠`

    output.name =

      `⁠beta10 for 0binomial observations⁠`

    output.name.intern =

      `⁠beta10 for 0binomial observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

Model '0binomialS'.
  Properties:
    doc =

      `⁠New 0-inflated Binomial Swap⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠TRUE⁠`

    link =

      `⁠default logit loga cauchit probit cloglog ccloglog loglog log⁠`

    link.simple =

      `⁠default logit cauchit probit cloglog ccloglog⁠`

    pdf =

      `⁠0inflated⁠`

  Number of hyperparmeters is 10.

  Hyperparameter 'theta1'
    hyperid =

      `⁠56501⁠`

    name =

      `⁠beta1⁠`

    short.name =

      `⁠beta1⁠`

    output.name =

      `⁠beta1 for 0binomialS observations⁠`

    output.name.intern =

      `⁠beta1 for 0binomialS observations⁠`

    initial =

      `⁠-4⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠-4 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠56502⁠`

    name =

      `⁠beta2⁠`

    short.name =

      `⁠beta2⁠`

    output.name =

      `⁠beta2 for 0binomialS observations⁠`

    output.name.intern =

      `⁠beta2 for 0binomialS observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta3'
    hyperid =

      `⁠56503⁠`

    name =

      `⁠beta3⁠`

    short.name =

      `⁠beta3⁠`

    output.name =

      `⁠beta3 for 0binomialS observations⁠`

    output.name.intern =

      `⁠beta3 for 0binomialS observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta4'
    hyperid =

      `⁠56504⁠`

    name =

      `⁠beta4⁠`

    short.name =

      `⁠beta4⁠`

    output.name =

      `⁠beta4 for 0binomialS observations⁠`

    output.name.intern =

      `⁠beta4 for 0binomialS observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta5'
    hyperid =

      `⁠56505⁠`

    name =

      `⁠beta5⁠`

    short.name =

      `⁠beta5⁠`

    output.name =

      `⁠beta5 for 0binomialS observations⁠`

    output.name.intern =

      `⁠beta5 for 0binomialS observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta6'
    hyperid =

      `⁠56506⁠`

    name =

      `⁠beta6⁠`

    short.name =

      `⁠beta6⁠`

    output.name =

      `⁠beta6 for 0binomialS observations⁠`

    output.name.intern =

      `⁠beta6 for 0binomialS observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta7'
    hyperid =

      `⁠56507⁠`

    name =

      `⁠beta7⁠`

    short.name =

      `⁠beta7⁠`

    output.name =

      `⁠beta7 for 0binomialS observations⁠`

    output.name.intern =

      `⁠beta7 for 0binomialS observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta8'
    hyperid =

      `⁠56508⁠`

    name =

      `⁠beta8⁠`

    short.name =

      `⁠beta8⁠`

    output.name =

      `⁠beta8 for 0binomialS observations⁠`

    output.name.intern =

      `⁠beta8 for 0binomialS observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta9'
    hyperid =

      `⁠56509⁠`

    name =

      `⁠beta9⁠`

    short.name =

      `⁠beta9⁠`

    output.name =

      `⁠beta9 for 0binomialS observations⁠`

    output.name.intern =

      `⁠beta9 for 0binomialS observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta10'
    hyperid =

      `⁠56510⁠`

    name =

      `⁠beta10⁠`

    short.name =

      `⁠beta10⁠`

    output.name =

      `⁠beta10 for 0binomialS observations⁠`

    output.name.intern =

      `⁠beta10 for 0binomialS observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

Model '0nbinomial'.
  Properties:
    doc =

      `⁠New 0-inflated nBinomial⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠TRUE⁠`

    link =

      `⁠default log⁠`

    link.simple =

      `⁠default logit cauchit probit cloglog ccloglog⁠`

    pdf =

      `⁠0inflated⁠`

  Number of hyperparmeters is 10.

  Hyperparameter 'theta1'
    hyperid =

      `⁠56421⁠`

    name =

      `⁠beta1⁠`

    short.name =

      `⁠beta1⁠`

    output.name =

      `⁠beta1 for 0nbinomial observations⁠`

    output.name.intern =

      `⁠beta1 for 0nbinomial observations⁠`

    initial =

      `⁠-4⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠-4 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠56422⁠`

    name =

      `⁠beta2⁠`

    short.name =

      `⁠beta2⁠`

    output.name =

      `⁠beta2 for 0nbinomial observations⁠`

    output.name.intern =

      `⁠beta2 for 0nbinomial observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta3'
    hyperid =

      `⁠56423⁠`

    name =

      `⁠beta3⁠`

    short.name =

      `⁠beta3⁠`

    output.name =

      `⁠beta3 for 0nbinomial observations⁠`

    output.name.intern =

      `⁠beta3 for 0nbinomial observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta4'
    hyperid =

      `⁠56424⁠`

    name =

      `⁠beta4⁠`

    short.name =

      `⁠beta4⁠`

    output.name =

      `⁠beta4 for 0nbinomial observations⁠`

    output.name.intern =

      `⁠beta4 for 0nbinomial observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta5'
    hyperid =

      `⁠56425⁠`

    name =

      `⁠beta5⁠`

    short.name =

      `⁠beta5⁠`

    output.name =

      `⁠beta5 for 0nbinomial observations⁠`

    output.name.intern =

      `⁠beta5 for 0nbinomial observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta6'
    hyperid =

      `⁠56426⁠`

    name =

      `⁠beta6⁠`

    short.name =

      `⁠beta6⁠`

    output.name =

      `⁠beta6 for 0nbinomial observations⁠`

    output.name.intern =

      `⁠beta6 for 0nbinomial observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta7'
    hyperid =

      `⁠56427⁠`

    name =

      `⁠beta7⁠`

    short.name =

      `⁠beta7⁠`

    output.name =

      `⁠beta7 for 0nbinomial observations⁠`

    output.name.intern =

      `⁠beta7 for 0nbinomial observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta8'
    hyperid =

      `⁠56428⁠`

    name =

      `⁠beta8⁠`

    short.name =

      `⁠beta8⁠`

    output.name =

      `⁠beta8 for 0nbinomial observations⁠`

    output.name.intern =

      `⁠beta8 for 0nbinomial observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta9'
    hyperid =

      `⁠56429⁠`

    name =

      `⁠beta9⁠`

    short.name =

      `⁠beta9⁠`

    output.name =

      `⁠beta9 for 0nbinomial observations⁠`

    output.name.intern =

      `⁠beta9 for 0nbinomial observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta10'
    hyperid =

      `⁠56430⁠`

    name =

      `⁠beta10⁠`

    short.name =

      `⁠beta10⁠`

    output.name =

      `⁠beta10 for 0nbinomial observations⁠`

    output.name.intern =

      `⁠beta10 for 0nbinomial observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

Model '0nbinomialS'.
  Properties:
    doc =

      `⁠New 0-inflated nBinomialS⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠TRUE⁠`

    link =

      `⁠default logit cauchit probit cloglog ccloglog⁠`

    link.simple =

      `⁠default log⁠`

    pdf =

      `⁠0inflated⁠`

  Number of hyperparmeters is 10.

  Hyperparameter 'theta1'
    hyperid =

      `⁠56441⁠`

    name =

      `⁠beta1⁠`

    short.name =

      `⁠beta1⁠`

    output.name =

      `⁠beta1 for 0nbinomialS observations⁠`

    output.name.intern =

      `⁠beta1 for 0nbinomialS observations⁠`

    initial =

      `⁠-4⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠-4 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠56442⁠`

    name =

      `⁠beta2⁠`

    short.name =

      `⁠beta2⁠`

    output.name =

      `⁠beta2 for 0nbinomialS observations⁠`

    output.name.intern =

      `⁠beta2 for 0nbinomialS observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta3'
    hyperid =

      `⁠56443⁠`

    name =

      `⁠beta3⁠`

    short.name =

      `⁠beta3⁠`

    output.name =

      `⁠beta3 for 0nbinomialS observations⁠`

    output.name.intern =

      `⁠beta3 for 0nbinomialS observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta4'
    hyperid =

      `⁠56444⁠`

    name =

      `⁠beta4⁠`

    short.name =

      `⁠beta4⁠`

    output.name =

      `⁠beta4 for 0nbinomialS observations⁠`

    output.name.intern =

      `⁠beta4 for 0nbinomialS observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta5'
    hyperid =

      `⁠56445⁠`

    name =

      `⁠beta5⁠`

    short.name =

      `⁠beta5⁠`

    output.name =

      `⁠beta5 for 0nbinomialS observations⁠`

    output.name.intern =

      `⁠beta5 for 0nbinomialS observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta6'
    hyperid =

      `⁠56446⁠`

    name =

      `⁠beta6⁠`

    short.name =

      `⁠beta6⁠`

    output.name =

      `⁠beta6 for 0nbinomialS observations⁠`

    output.name.intern =

      `⁠beta6 for 0nbinomialS observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta7'
    hyperid =

      `⁠56447⁠`

    name =

      `⁠beta7⁠`

    short.name =

      `⁠beta7⁠`

    output.name =

      `⁠beta7 for 0nbinomialS observations⁠`

    output.name.intern =

      `⁠beta7 for 0nbinomialS observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta8'
    hyperid =

      `⁠56448⁠`

    name =

      `⁠beta8⁠`

    short.name =

      `⁠beta8⁠`

    output.name =

      `⁠beta8 for 0nbinomialS observations⁠`

    output.name.intern =

      `⁠beta8 for 0nbinomialS observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta9'
    hyperid =

      `⁠56449⁠`

    name =

      `⁠beta9⁠`

    short.name =

      `⁠beta9⁠`

    output.name =

      `⁠beta9 for 0nbinomialS observations⁠`

    output.name.intern =

      `⁠beta9 for 0nbinomialS observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta10'
    hyperid =

      `⁠56450⁠`

    name =

      `⁠beta10⁠`

    short.name =

      `⁠beta10⁠`

    output.name =

      `⁠beta10 for 0nbinomialS observations⁠`

    output.name.intern =

      `⁠beta10 for 0nbinomialS observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

Model 'binomialmix'.
  Properties:
    doc =

      `⁠Binomial mixture⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠TRUE⁠`

    link =

      `⁠default logit probit⁠`

    pdf =

      `⁠binomialmix⁠`

  Number of hyperparmeters is 51.

  Hyperparameter 'theta1'
    hyperid =

      `⁠56551⁠`

    name =

      `⁠beta1⁠`

    short.name =

      `⁠beta1⁠`

    output.name =

      `⁠beta1 for binomialmix observations⁠`

    output.name.intern =

      `⁠beta1 for binomialmix observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠56552⁠`

    name =

      `⁠beta2⁠`

    short.name =

      `⁠beta2⁠`

    output.name =

      `⁠beta2 for binomialmix observations⁠`

    output.name.intern =

      `⁠beta2 for binomialmix observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta3'
    hyperid =

      `⁠56553⁠`

    name =

      `⁠beta3⁠`

    short.name =

      `⁠beta3⁠`

    output.name =

      `⁠beta3 for binomialmix observations⁠`

    output.name.intern =

      `⁠beta3 for binomialmix observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta4'
    hyperid =

      `⁠56554⁠`

    name =

      `⁠beta4⁠`

    short.name =

      `⁠beta4⁠`

    output.name =

      `⁠beta4 for binomialmix observations⁠`

    output.name.intern =

      `⁠beta4 for binomialmix observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta5'
    hyperid =

      `⁠56555⁠`

    name =

      `⁠beta5⁠`

    short.name =

      `⁠beta5⁠`

    output.name =

      `⁠beta5 for binomialmix observations⁠`

    output.name.intern =

      `⁠beta5 for binomialmix observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta6'
    hyperid =

      `⁠56556⁠`

    name =

      `⁠beta6⁠`

    short.name =

      `⁠beta6⁠`

    output.name =

      `⁠beta6 for binomialmix observations⁠`

    output.name.intern =

      `⁠beta6 for binomialmix observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta7'
    hyperid =

      `⁠56557⁠`

    name =

      `⁠beta7⁠`

    short.name =

      `⁠beta7⁠`

    output.name =

      `⁠beta7 for binomialmix observations⁠`

    output.name.intern =

      `⁠beta7 for binomialmix observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta8'
    hyperid =

      `⁠56558⁠`

    name =

      `⁠beta8⁠`

    short.name =

      `⁠beta8⁠`

    output.name =

      `⁠beta8 for binomialmix observations⁠`

    output.name.intern =

      `⁠beta8 for binomialmix observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta9'
    hyperid =

      `⁠56559⁠`

    name =

      `⁠beta9⁠`

    short.name =

      `⁠beta9⁠`

    output.name =

      `⁠beta9 for binomialmix observations⁠`

    output.name.intern =

      `⁠beta9 for binomialmix observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta10'
    hyperid =

      `⁠56560⁠`

    name =

      `⁠beta10⁠`

    short.name =

      `⁠beta10⁠`

    output.name =

      `⁠beta10 for binomialmix observations⁠`

    output.name.intern =

      `⁠beta10 for binomialmix observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta11'
    hyperid =

      `⁠56561⁠`

    name =

      `⁠beta11⁠`

    short.name =

      `⁠beta11⁠`

    output.name =

      `⁠beta11 for binomialmix observations⁠`

    output.name.intern =

      `⁠beta11 for binomialmix observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta12'
    hyperid =

      `⁠56562⁠`

    name =

      `⁠beta12⁠`

    short.name =

      `⁠beta12⁠`

    output.name =

      `⁠beta12 for binomialmix observations⁠`

    output.name.intern =

      `⁠beta12 for binomialmix observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta13'
    hyperid =

      `⁠56563⁠`

    name =

      `⁠beta13⁠`

    short.name =

      `⁠beta13⁠`

    output.name =

      `⁠beta13 for binomialmix observations⁠`

    output.name.intern =

      `⁠beta13 for binomialmix observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta14'
    hyperid =

      `⁠56564⁠`

    name =

      `⁠beta14⁠`

    short.name =

      `⁠beta14⁠`

    output.name =

      `⁠beta14 for binomialmix observations⁠`

    output.name.intern =

      `⁠beta14 for binomialmix observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta15'
    hyperid =

      `⁠56565⁠`

    name =

      `⁠beta15⁠`

    short.name =

      `⁠beta15⁠`

    output.name =

      `⁠beta15 for binomialmix observations⁠`

    output.name.intern =

      `⁠beta15 for binomialmix observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta16'
    hyperid =

      `⁠56566⁠`

    name =

      `⁠beta16⁠`

    short.name =

      `⁠beta16⁠`

    output.name =

      `⁠beta16 for binomialmix observations⁠`

    output.name.intern =

      `⁠beta16 for binomialmix observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta17'
    hyperid =

      `⁠56567⁠`

    name =

      `⁠beta17⁠`

    short.name =

      `⁠beta17⁠`

    output.name =

      `⁠beta17 for binomialmix observations⁠`

    output.name.intern =

      `⁠beta17 for binomialmix observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta18'
    hyperid =

      `⁠56568⁠`

    name =

      `⁠beta18⁠`

    short.name =

      `⁠beta18⁠`

    output.name =

      `⁠beta18 for binomialmix observations⁠`

    output.name.intern =

      `⁠beta18 for binomialmix observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta19'
    hyperid =

      `⁠56569⁠`

    name =

      `⁠beta19⁠`

    short.name =

      `⁠beta19⁠`

    output.name =

      `⁠beta19 for binomialmix observations⁠`

    output.name.intern =

      `⁠beta19 for binomialmix observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta20'
    hyperid =

      `⁠56570⁠`

    name =

      `⁠beta20⁠`

    short.name =

      `⁠beta20⁠`

    output.name =

      `⁠beta20 for binomialmix observations⁠`

    output.name.intern =

      `⁠beta20 for binomialmix observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta21'
    hyperid =

      `⁠56571⁠`

    name =

      `⁠beta21⁠`

    short.name =

      `⁠beta21⁠`

    output.name =

      `⁠beta21 for binomialmix observations⁠`

    output.name.intern =

      `⁠beta21 for binomialmix observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta22'
    hyperid =

      `⁠56572⁠`

    name =

      `⁠beta22⁠`

    short.name =

      `⁠beta22⁠`

    output.name =

      `⁠beta22 for binomialmix observations⁠`

    output.name.intern =

      `⁠beta22 for binomialmix observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta23'
    hyperid =

      `⁠56573⁠`

    name =

      `⁠beta23⁠`

    short.name =

      `⁠beta23⁠`

    output.name =

      `⁠beta23 for binomialmix observations⁠`

    output.name.intern =

      `⁠beta23 for binomialmix observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta24'
    hyperid =

      `⁠56574⁠`

    name =

      `⁠beta24⁠`

    short.name =

      `⁠beta24⁠`

    output.name =

      `⁠beta24 for binomialmix observations⁠`

    output.name.intern =

      `⁠beta24 for binomialmix observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta25'
    hyperid =

      `⁠56575⁠`

    name =

      `⁠beta25⁠`

    short.name =

      `⁠beta25⁠`

    output.name =

      `⁠beta25 for binomialmix observations⁠`

    output.name.intern =

      `⁠beta25 for binomialmix observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta26'
    hyperid =

      `⁠56576⁠`

    name =

      `⁠beta26⁠`

    short.name =

      `⁠beta26⁠`

    output.name =

      `⁠beta26 for binomialmix observations⁠`

    output.name.intern =

      `⁠beta26 for binomialmix observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta27'
    hyperid =

      `⁠56577⁠`

    name =

      `⁠beta27⁠`

    short.name =

      `⁠beta27⁠`

    output.name =

      `⁠beta27 for binomialmix observations⁠`

    output.name.intern =

      `⁠beta27 for binomialmix observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta28'
    hyperid =

      `⁠56578⁠`

    name =

      `⁠beta28⁠`

    short.name =

      `⁠beta28⁠`

    output.name =

      `⁠beta28 for binomialmix observations⁠`

    output.name.intern =

      `⁠beta28 for binomialmix observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta29'
    hyperid =

      `⁠56579⁠`

    name =

      `⁠beta29⁠`

    short.name =

      `⁠beta29⁠`

    output.name =

      `⁠beta29 for binomialmix observations⁠`

    output.name.intern =

      `⁠beta29 for binomialmix observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta30'
    hyperid =

      `⁠56580⁠`

    name =

      `⁠beta30⁠`

    short.name =

      `⁠beta30⁠`

    output.name =

      `⁠beta30 for binomialmix observations⁠`

    output.name.intern =

      `⁠beta30 for binomialmix observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta31'
    hyperid =

      `⁠56581⁠`

    name =

      `⁠beta31⁠`

    short.name =

      `⁠beta31⁠`

    output.name =

      `⁠beta31 for binomialmix observations⁠`

    output.name.intern =

      `⁠beta31 for binomialmix observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta32'
    hyperid =

      `⁠56582⁠`

    name =

      `⁠beta32⁠`

    short.name =

      `⁠beta32⁠`

    output.name =

      `⁠beta32 for binomialmix observations⁠`

    output.name.intern =

      `⁠beta32 for binomialmix observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta33'
    hyperid =

      `⁠56583⁠`

    name =

      `⁠beta33⁠`

    short.name =

      `⁠beta33⁠`

    output.name =

      `⁠beta33 for binomialmix observations⁠`

    output.name.intern =

      `⁠beta33 for binomialmix observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta34'
    hyperid =

      `⁠56584⁠`

    name =

      `⁠beta34⁠`

    short.name =

      `⁠beta34⁠`

    output.name =

      `⁠beta34 for binomialmix observations⁠`

    output.name.intern =

      `⁠beta34 for binomialmix observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta35'
    hyperid =

      `⁠56585⁠`

    name =

      `⁠beta35⁠`

    short.name =

      `⁠beta35⁠`

    output.name =

      `⁠beta35 for binomialmix observations⁠`

    output.name.intern =

      `⁠beta35 for binomialmix observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta36'
    hyperid =

      `⁠56586⁠`

    name =

      `⁠beta36⁠`

    short.name =

      `⁠beta36⁠`

    output.name =

      `⁠beta36 for binomialmix observations⁠`

    output.name.intern =

      `⁠beta36 for binomialmix observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta37'
    hyperid =

      `⁠56587⁠`

    name =

      `⁠beta37⁠`

    short.name =

      `⁠beta37⁠`

    output.name =

      `⁠beta37 for binomialmix observations⁠`

    output.name.intern =

      `⁠beta37 for binomialmix observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta38'
    hyperid =

      `⁠56588⁠`

    name =

      `⁠beta38⁠`

    short.name =

      `⁠beta38⁠`

    output.name =

      `⁠beta38 for binomialmix observations⁠`

    output.name.intern =

      `⁠beta38 for binomialmix observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta39'
    hyperid =

      `⁠56589⁠`

    name =

      `⁠beta39⁠`

    short.name =

      `⁠beta39⁠`

    output.name =

      `⁠beta39 for binomialmix observations⁠`

    output.name.intern =

      `⁠beta39 for binomialmix observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta40'
    hyperid =

      `⁠56590⁠`

    name =

      `⁠beta40⁠`

    short.name =

      `⁠beta40⁠`

    output.name =

      `⁠beta40 for binomialmix observations⁠`

    output.name.intern =

      `⁠beta40 for binomialmix observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta41'
    hyperid =

      `⁠56591⁠`

    name =

      `⁠beta41⁠`

    short.name =

      `⁠beta41⁠`

    output.name =

      `⁠beta41 for binomialmix observations⁠`

    output.name.intern =

      `⁠beta41 for binomialmix observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta42'
    hyperid =

      `⁠56592⁠`

    name =

      `⁠beta42⁠`

    short.name =

      `⁠beta42⁠`

    output.name =

      `⁠beta42 for binomialmix observations⁠`

    output.name.intern =

      `⁠beta42 for binomialmix observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta43'
    hyperid =

      `⁠56593⁠`

    name =

      `⁠beta43⁠`

    short.name =

      `⁠beta43⁠`

    output.name =

      `⁠beta43 for binomialmix observations⁠`

    output.name.intern =

      `⁠beta43 for binomialmix observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta44'
    hyperid =

      `⁠56594⁠`

    name =

      `⁠beta44⁠`

    short.name =

      `⁠beta44⁠`

    output.name =

      `⁠beta44 for binomialmix observations⁠`

    output.name.intern =

      `⁠beta44 for binomialmix observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta45'
    hyperid =

      `⁠56595⁠`

    name =

      `⁠beta45⁠`

    short.name =

      `⁠beta45⁠`

    output.name =

      `⁠beta45 for binomialmix observations⁠`

    output.name.intern =

      `⁠beta45 for binomialmix observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta46'
    hyperid =

      `⁠56596⁠`

    name =

      `⁠beta46⁠`

    short.name =

      `⁠beta46⁠`

    output.name =

      `⁠beta46 for binomialmix observations⁠`

    output.name.intern =

      `⁠beta46 for binomialmix observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta47'
    hyperid =

      `⁠56597⁠`

    name =

      `⁠beta47⁠`

    short.name =

      `⁠beta47⁠`

    output.name =

      `⁠beta47 for binomialmix observations⁠`

    output.name.intern =

      `⁠beta47 for binomialmix observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta48'
    hyperid =

      `⁠56598⁠`

    name =

      `⁠beta48⁠`

    short.name =

      `⁠beta48⁠`

    output.name =

      `⁠beta48 for binomialmix observations⁠`

    output.name.intern =

      `⁠beta48 for binomialmix observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta49'
    hyperid =

      `⁠56599⁠`

    name =

      `⁠beta49⁠`

    short.name =

      `⁠beta49⁠`

    output.name =

      `⁠beta49 for binomialmix observations⁠`

    output.name.intern =

      `⁠beta49 for binomialmix observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta50'
    hyperid =

      `⁠56600⁠`

    name =

      `⁠beta50⁠`

    short.name =

      `⁠beta50⁠`

    output.name =

      `⁠beta50 for binomialmix observations⁠`

    output.name.intern =

      `⁠beta50 for binomialmix observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta51'
    hyperid =

      `⁠56601⁠`

    name =

      `⁠beta51⁠`

    short.name =

      `⁠beta51⁠`

    output.name =

      `⁠beta51 for binomialmix observations⁠`

    output.name.intern =

      `⁠beta51 for binomialmix observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

Model 'binomial'.
  Properties:
    doc =

      `⁠The Binomial likelihood⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠TRUE⁠`

    link =

      `⁠default logit loga cauchit probit cloglog ccloglog loglog log sslogit logitoffset quantile pquantile robit sn powerlogit gevit cgevit⁠`

    pdf =

      `⁠binomial⁠`

  Number of hyperparmeters is 0.

Model 'xbinomial'.
  Properties:
    doc =

      `⁠The Binomial likelihood (experimental version)⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠TRUE⁠`

    link =

      `⁠default logit loga cauchit probit cloglog ccloglog loglog log sslogit logitoffset quantile pquantile robit sn powerlogit gevit cgevit⁠`

    pdf =

      `⁠binomial⁠`

  Number of hyperparmeters is 0.

Model 'occupancy'.
  Properties:
    doc =

      `⁠Occupancy likelihood⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠TRUE⁠`

    link =

      `⁠default logit cloglog⁠`

    link.simple =

      `⁠default logit cloglog⁠`

    pdf =

      `⁠occupancy⁠`

  Number of hyperparmeters is 10.

  Hyperparameter 'theta1'
    hyperid =

      `⁠56601⁠`

    name =

      `⁠beta1⁠`

    short.name =

      `⁠beta1⁠`

    output.name =

      `⁠beta1 for occupancy observations⁠`

    output.name.intern =

      `⁠beta1 for occupancy observations⁠`

    initial =

      `⁠-2⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠-2 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠56602⁠`

    name =

      `⁠beta2⁠`

    short.name =

      `⁠beta2⁠`

    output.name =

      `⁠beta2 for occupancy observations⁠`

    output.name.intern =

      `⁠beta2 for occupancy observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta3'
    hyperid =

      `⁠56603⁠`

    name =

      `⁠beta3⁠`

    short.name =

      `⁠beta3⁠`

    output.name =

      `⁠beta3 for occupancy observations⁠`

    output.name.intern =

      `⁠beta3 for occupancy observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta4'
    hyperid =

      `⁠56604⁠`

    name =

      `⁠beta4⁠`

    short.name =

      `⁠beta4⁠`

    output.name =

      `⁠beta4 for occupancy observations⁠`

    output.name.intern =

      `⁠beta4 for occupancy observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta5'
    hyperid =

      `⁠56605⁠`

    name =

      `⁠beta5⁠`

    short.name =

      `⁠beta5⁠`

    output.name =

      `⁠beta5 for occupancy observations⁠`

    output.name.intern =

      `⁠beta5 for occupancy observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta6'
    hyperid =

      `⁠56606⁠`

    name =

      `⁠beta6⁠`

    short.name =

      `⁠beta6⁠`

    output.name =

      `⁠beta6 for occupancy observations⁠`

    output.name.intern =

      `⁠beta6 for occupancy observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta7'
    hyperid =

      `⁠56607⁠`

    name =

      `⁠beta7⁠`

    short.name =

      `⁠beta7⁠`

    output.name =

      `⁠beta7 for occupancy observations⁠`

    output.name.intern =

      `⁠beta7 for occupancy observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta8'
    hyperid =

      `⁠56608⁠`

    name =

      `⁠beta8⁠`

    short.name =

      `⁠beta8⁠`

    output.name =

      `⁠beta8 for occupancy observations⁠`

    output.name.intern =

      `⁠beta8 for occupancy observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta9'
    hyperid =

      `⁠56609⁠`

    name =

      `⁠beta9⁠`

    short.name =

      `⁠beta9⁠`

    output.name =

      `⁠beta9 for occupancy observations⁠`

    output.name.intern =

      `⁠beta9 for occupancy observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta10'
    hyperid =

      `⁠56610⁠`

    name =

      `⁠beta10⁠`

    short.name =

      `⁠beta10⁠`

    output.name =

      `⁠beta10 for occupancy observations⁠`

    output.name.intern =

      `⁠beta10 for occupancy observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

Model 'pom'.
  Properties:
    doc =

      `⁠Likelihood for the proportional odds model⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠TRUE⁠`

    link =

      `⁠default identity⁠`

    pdf =

      `⁠pom⁠`

  Number of hyperparmeters is 10.

  Hyperparameter 'theta1'
    hyperid =

      `⁠57101⁠`

    name =

      `⁠theta1⁠`

    short.name =

      `⁠theta1⁠`

    output.name =

      `⁠theta1 for POM⁠`

    output.name.intern =

      `⁠theta1 for POM⁠`

    initial =

      `⁠NA⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠dirichlet⁠`

    param =

      `⁠3⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠57102⁠`

    name =

      `⁠theta2⁠`

    short.name =

      `⁠theta2⁠`

    output.name =

      `⁠theta2 for POM⁠`

    output.name.intern =

      `⁠theta2 for POM⁠`

    initial =

      `⁠NA⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta3'
    hyperid =

      `⁠57103⁠`

    name =

      `⁠theta3⁠`

    short.name =

      `⁠theta3⁠`

    output.name =

      `⁠theta3 for POM⁠`

    output.name.intern =

      `⁠theta3 for POM⁠`

    initial =

      `⁠NA⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta4'
    hyperid =

      `⁠57104⁠`

    name =

      `⁠theta4⁠`

    short.name =

      `⁠theta4⁠`

    output.name =

      `⁠theta4 for POM⁠`

    output.name.intern =

      `⁠theta4 for POM⁠`

    initial =

      `⁠NA⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta5'
    hyperid =

      `⁠57105⁠`

    name =

      `⁠theta5⁠`

    short.name =

      `⁠theta5⁠`

    output.name =

      `⁠theta5 for POM⁠`

    output.name.intern =

      `⁠theta5 for POM⁠`

    initial =

      `⁠NA⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta6'
    hyperid =

      `⁠57106⁠`

    name =

      `⁠theta6⁠`

    short.name =

      `⁠theta6⁠`

    output.name =

      `⁠theta6 for POM⁠`

    output.name.intern =

      `⁠theta6 for POM⁠`

    initial =

      `⁠NA⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta7'
    hyperid =

      `⁠57107⁠`

    name =

      `⁠theta7⁠`

    short.name =

      `⁠theta7⁠`

    output.name =

      `⁠theta7 for POM⁠`

    output.name.intern =

      `⁠theta7 for POM⁠`

    initial =

      `⁠NA⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta8'
    hyperid =

      `⁠57108⁠`

    name =

      `⁠theta8⁠`

    short.name =

      `⁠theta8⁠`

    output.name =

      `⁠theta8 for POM⁠`

    output.name.intern =

      `⁠theta8 for POM⁠`

    initial =

      `⁠NA⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta9'
    hyperid =

      `⁠57109⁠`

    name =

      `⁠theta9⁠`

    short.name =

      `⁠theta9⁠`

    output.name =

      `⁠theta9 for POM⁠`

    output.name.intern =

      `⁠theta9 for POM⁠`

    initial =

      `⁠NA⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta10'
    hyperid =

      `⁠57110⁠`

    name =

      `⁠theta10⁠`

    short.name =

      `⁠theta10⁠`

    output.name =

      `⁠theta10 for POM⁠`

    output.name.intern =

      `⁠theta10 for POM⁠`

    initial =

      `⁠NA⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

Model 'bgev'.
  Properties:
    doc =

      `⁠The blended Generalized Extreme Value likelihood⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠FALSE⁠`

    link =

      `⁠default identity log⁠`

    pdf =

      `⁠bgev⁠`

  Number of hyperparmeters is 12.

  Hyperparameter 'theta1'
    hyperid =

      `⁠57201⁠`

    name =

      `⁠spread⁠`

    short.name =

      `⁠sd⁠`

    output.name =

      `⁠spread for BGEV observations⁠`

    output.name.intern =

      `⁠log spread for BGEV observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 3⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠57202⁠`

    name =

      `⁠tail⁠`

    short.name =

      `⁠xi⁠`

    output.name =

      `⁠tail for BGEV observations⁠`

    output.name.intern =

      `⁠intern tail for BGEV observations⁠`

    initial =

      `⁠-4⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠pc.gevtail⁠`

    param =

      `⁠7 0 0.5⁠`

    to.theta =

      `⁠function(x, interval = c(REPLACE.ME.low, REPLACE.ME.high)) log(-(interval[1] - x) / (interval[2] - x))⁠`

    from.theta =

      `⁠function(x, interval = c(REPLACE.ME.low, REPLACE.ME.high)) interval[1] + (interval[2] - interval[1]) * exp(x) / (1.0 + exp(x))⁠`

  Hyperparameter 'theta3'
    hyperid =

      `⁠57203⁠`

    name =

      `⁠beta1⁠`

    short.name =

      `⁠beta1⁠`

    output.name =

      `⁠MUST BE FIXED⁠`

    output.name.intern =

      `⁠MUST BE FIXED⁠`

    initial =

      `⁠NA⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 300⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta4'
    hyperid =

      `⁠57204⁠`

    name =

      `⁠beta2⁠`

    short.name =

      `⁠beta2⁠`

    output.name =

      `⁠MUST BE FIXED⁠`

    output.name.intern =

      `⁠MUST BE FIXED⁠`

    initial =

      `⁠NA⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 300⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta5'
    hyperid =

      `⁠57205⁠`

    name =

      `⁠beta3⁠`

    short.name =

      `⁠beta3⁠`

    output.name =

      `⁠MUST BE FIXED⁠`

    output.name.intern =

      `⁠MUST BE FIXED⁠`

    initial =

      `⁠NA⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 300⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta6'
    hyperid =

      `⁠57206⁠`

    name =

      `⁠beta4⁠`

    short.name =

      `⁠beta4⁠`

    output.name =

      `⁠MUST BE FIXED⁠`

    output.name.intern =

      `⁠MUST BE FIXED⁠`

    initial =

      `⁠NA⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 300⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta7'
    hyperid =

      `⁠57207⁠`

    name =

      `⁠beta5⁠`

    short.name =

      `⁠beta5⁠`

    output.name =

      `⁠MUST BE FIXED⁠`

    output.name.intern =

      `⁠MUST BE FIXED⁠`

    initial =

      `⁠NA⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 300⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta8'
    hyperid =

      `⁠57208⁠`

    name =

      `⁠beta6⁠`

    short.name =

      `⁠beta6⁠`

    output.name =

      `⁠MUST BE FIXED⁠`

    output.name.intern =

      `⁠MUST BE FIXED⁠`

    initial =

      `⁠NA⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 300⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta9'
    hyperid =

      `⁠57209⁠`

    name =

      `⁠beta7⁠`

    short.name =

      `⁠beta7⁠`

    output.name =

      `⁠MUST BE FIXED⁠`

    output.name.intern =

      `⁠MUST BE FIXED⁠`

    initial =

      `⁠NA⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 300⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta10'
    hyperid =

      `⁠57210⁠`

    name =

      `⁠beta8⁠`

    short.name =

      `⁠beta8⁠`

    output.name =

      `⁠MUST BE FIXED⁠`

    output.name.intern =

      `⁠MUST BE FIXED⁠`

    initial =

      `⁠NA⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 300⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta11'
    hyperid =

      `⁠57211⁠`

    name =

      `⁠beta9⁠`

    short.name =

      `⁠beta9⁠`

    output.name =

      `⁠MUST BE FIXED⁠`

    output.name.intern =

      `⁠MUST BE FIXED⁠`

    initial =

      `⁠NA⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 300⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta12'
    hyperid =

      `⁠57212⁠`

    name =

      `⁠beta10⁠`

    short.name =

      `⁠beta⁠`

    output.name =

      `⁠MUST BE FIXED⁠`

    output.name.intern =

      `⁠MUST BE FIXED⁠`

    initial =

      `⁠NA⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 300⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

Model 'gamma'.
  Properties:
    doc =

      `⁠The Gamma likelihood⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠FALSE⁠`

    link =

      `⁠default log quantile⁠`

    pdf =

      `⁠gamma⁠`

  Number of hyperparmeters is 1.

  Hyperparameter 'theta'
    hyperid =

      `⁠58001⁠`

    name =

      `⁠precision parameter⁠`

    short.name =

      `⁠prec⁠`

    output.name =

      `⁠Precision-parameter for the Gamma observations⁠`

    output.name.intern =

      `⁠Intern precision-parameter for the Gamma observations⁠`

    initial =

      `⁠4.60517018598809⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 0.01⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

Model 'mgamma'.
  Properties:
    doc =

      `⁠The modal Gamma likelihood⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠FALSE⁠`

    link =

      `⁠default log⁠`

    pdf =

      `⁠mgamma⁠`

  Number of hyperparmeters is 1.

  Hyperparameter 'theta'
    hyperid =

      `⁠58002⁠`

    name =

      `⁠precision parameter⁠`

    short.name =

      `⁠prec⁠`

    output.name =

      `⁠Precision-parameter for the modal Gamma observations⁠`

    output.name.intern =

      `⁠Intern precision-parameter for the modal Gamma observations⁠`

    initial =

      `⁠4.60517018598809⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 0.01⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

Model 'gammasv'.
  Properties:
    doc =

      `⁠The Gamma likelihood with constant rate⁠`

    status =

      `⁠experimental⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠FALSE⁠`

    link =

      `⁠default log⁠`

    pdf =

      `⁠gammasv⁠`

  Number of hyperparmeters is 1.

  Hyperparameter 'theta'
    hyperid =

      `⁠58003⁠`

    name =

      `⁠precision parameter⁠`

    short.name =

      `⁠prec⁠`

    output.name =

      `⁠Precision-parameter for the Gammasv observations⁠`

    output.name.intern =

      `⁠Intern precision-parameter for the Gammasv observations⁠`

    initial =

      `⁠4.60517018598809⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 0.01⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

Model 'gammasurv'.
  Properties:
    doc =

      `⁠The Gamma likelihood (survival)⁠`

    survival =

      `⁠TRUE⁠`

    discrete =

      `⁠FALSE⁠`

    link =

      `⁠default log neglog quantile⁠`

    pdf =

      `⁠gammasurv⁠`

  Number of hyperparmeters is 11.

  Hyperparameter 'theta1'
    hyperid =

      `⁠58101⁠`

    name =

      `⁠precision parameter⁠`

    short.name =

      `⁠prec⁠`

    output.name =

      `⁠Precision-parameter for the Gamma surv observations⁠`

    output.name.intern =

      `⁠Intern precision-parameter for the Gamma surv observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 0.01⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠58102⁠`

    name =

      `⁠beta1⁠`

    short.name =

      `⁠beta1⁠`

    output.name =

      `⁠beta1 for Gamma-Cure⁠`

    output.name.intern =

      `⁠beta1 for Gamma-Cure⁠`

    initial =

      `⁠-7⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠-4 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta3'
    hyperid =

      `⁠58103⁠`

    name =

      `⁠beta2⁠`

    short.name =

      `⁠beta2⁠`

    output.name =

      `⁠beta2 for Gamma-Cure⁠`

    output.name.intern =

      `⁠beta2 for Gamma-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta4'
    hyperid =

      `⁠58104⁠`

    name =

      `⁠beta3⁠`

    short.name =

      `⁠beta3⁠`

    output.name =

      `⁠beta3 for Gamma-Cure⁠`

    output.name.intern =

      `⁠beta3 for Gamma-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta5'
    hyperid =

      `⁠58105⁠`

    name =

      `⁠beta4⁠`

    short.name =

      `⁠beta4⁠`

    output.name =

      `⁠beta4 for Ga mma-Cure⁠`

    output.name.intern =

      `⁠beta4 for Gamma-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta6'
    hyperid =

      `⁠58106⁠`

    name =

      `⁠beta5⁠`

    short.name =

      `⁠beta5⁠`

    output.name =

      `⁠beta5 for Gamma-Cure⁠`

    output.name.intern =

      `⁠beta5 for Gamma-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta7'
    hyperid =

      `⁠58107⁠`

    name =

      `⁠beta6⁠`

    short.name =

      `⁠beta6⁠`

    output.name =

      `⁠beta6 for Gamma-Cure⁠`

    output.name.intern =

      `⁠beta6 for Gamma-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta8'
    hyperid =

      `⁠58108⁠`

    name =

      `⁠beta7⁠`

    short.name =

      `⁠beta7⁠`

    output.name =

      `⁠beta7 for Gamma-Cure⁠`

    output.name.intern =

      `⁠beta7 for Gamma-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta9'
    hyperid =

      `⁠58109⁠`

    name =

      `⁠beta8⁠`

    short.name =

      `⁠beta8⁠`

    output.name =

      `⁠beta8 for Gamma-Cure⁠`

    output.name.intern =

      `⁠beta8 for Gamma-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta10'
    hyperid =

      `⁠58110⁠`

    name =

      `⁠beta9⁠`

    short.name =

      `⁠beta9⁠`

    output.name =

      `⁠beta9 for Gamma-Cure⁠`

    output.name.intern =

      `⁠beta9 for Gamma-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta11'
    hyperid =

      `⁠58111⁠`

    name =

      `⁠beta10⁠`

    short.name =

      `⁠beta10⁠`

    output.name =

      `⁠beta10 for Gamma-Cure⁠`

    output.name.intern =

      `⁠beta10 for Gamma-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

Model 'mgammasurv'.
  Properties:
    doc =

      `⁠The modal Gamma likelihood (survival)⁠`

    survival =

      `⁠TRUE⁠`

    discrete =

      `⁠FALSE⁠`

    link =

      `⁠default log neglog⁠`

    pdf =

      `⁠agamma⁠`

  Number of hyperparmeters is 11.

  Hyperparameter 'theta1'
    hyperid =

      `⁠58121⁠`

    name =

      `⁠precision parameter⁠`

    short.name =

      `⁠prec⁠`

    output.name =

      `⁠Precision-parameter for the modal Gamma surv observations⁠`

    output.name.intern =

      `⁠Intern precision-parameter for the modal Gamma surv observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 0.01⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠58122⁠`

    name =

      `⁠beta1⁠`

    short.name =

      `⁠beta1⁠`

    output.name =

      `⁠beta1 for modal Gamma-Cure⁠`

    output.name.intern =

      `⁠beta1 for modal Gamma-Cure⁠`

    initial =

      `⁠-7⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠-4 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta3'
    hyperid =

      `⁠58123⁠`

    name =

      `⁠beta2⁠`

    short.name =

      `⁠beta2⁠`

    output.name =

      `⁠beta2 for modal Gamma-Cure⁠`

    output.name.intern =

      `⁠beta2 for modal Gamma-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta4'
    hyperid =

      `⁠58124⁠`

    name =

      `⁠beta3⁠`

    short.name =

      `⁠beta3⁠`

    output.name =

      `⁠beta3 for modal Gamma-Cure⁠`

    output.name.intern =

      `⁠beta3 for modal Gamma-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta5'
    hyperid =

      `⁠58125⁠`

    name =

      `⁠beta4⁠`

    short.name =

      `⁠beta4⁠`

    output.name =

      `⁠beta4 for Ga mma-Cure⁠`

    output.name.intern =

      `⁠beta4 for modal Gamma-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta6'
    hyperid =

      `⁠58126⁠`

    name =

      `⁠beta5⁠`

    short.name =

      `⁠beta5⁠`

    output.name =

      `⁠beta5 for modal Gamma-Cure⁠`

    output.name.intern =

      `⁠beta5 for modal Gamma-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta7'
    hyperid =

      `⁠58127⁠`

    name =

      `⁠beta6⁠`

    short.name =

      `⁠beta6⁠`

    output.name =

      `⁠beta6 for modal Gamma-Cure⁠`

    output.name.intern =

      `⁠beta6 for modal Gamma-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta8'
    hyperid =

      `⁠58128⁠`

    name =

      `⁠beta7⁠`

    short.name =

      `⁠beta7⁠`

    output.name =

      `⁠beta7 for modal Gamma-Cure⁠`

    output.name.intern =

      `⁠beta7 for modal Gamma-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta9'
    hyperid =

      `⁠58129⁠`

    name =

      `⁠beta8⁠`

    short.name =

      `⁠beta8⁠`

    output.name =

      `⁠beta8 for modal Gamma-Cure⁠`

    output.name.intern =

      `⁠beta8 for modal Gamma-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta10'
    hyperid =

      `⁠58130⁠`

    name =

      `⁠beta9⁠`

    short.name =

      `⁠beta9⁠`

    output.name =

      `⁠beta9 for modal Gamma-Cure⁠`

    output.name.intern =

      `⁠beta9 for modal Gamma-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta11'
    hyperid =

      `⁠58131⁠`

    name =

      `⁠beta10⁠`

    short.name =

      `⁠beta10⁠`

    output.name =

      `⁠beta10 for modal Gamma-Cure⁠`

    output.name.intern =

      `⁠beta10 for modal Gamma-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

Model 'gammajw'.
  Properties:
    doc =

      `⁠A special case of the Gamma likelihood⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠FALSE⁠`

    link =

      `⁠default log neglog⁠`

    pdf =

      `⁠gammajw⁠`

  Number of hyperparmeters is 0.

Model 'gammajwsurv'.
  Properties:
    doc =

      `⁠A special case of the Gamma likelihood (survival)⁠`

    survival =

      `⁠TRUE⁠`

    discrete =

      `⁠FALSE⁠`

    link =

      `⁠default log⁠`

    pdf =

      `⁠gammajw⁠`

  Number of hyperparmeters is 10.

  Hyperparameter 'theta1'
    hyperid =

      `⁠58200⁠`

    name =

      `⁠beta1⁠`

    short.name =

      `⁠beta1⁠`

    output.name =

      `⁠beta1 for GammaJW-Cure⁠`

    output.name.intern =

      `⁠beta1 for GammaJW-Cure⁠`

    initial =

      `⁠-7⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠-4 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠58201⁠`

    name =

      `⁠beta2⁠`

    short.name =

      `⁠beta2⁠`

    output.name =

      `⁠beta1 for GammaJW-Cure⁠`

    output.name.intern =

      `⁠beta1 for GammaJW-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta3'
    hyperid =

      `⁠58202⁠`

    name =

      `⁠beta3⁠`

    short.name =

      `⁠beta3⁠`

    output.name =

      `⁠beta3 for GammaJW-Cure⁠`

    output.name.intern =

      `⁠beta3 for GammaJW-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta4'
    hyperid =

      `⁠58203⁠`

    name =

      `⁠beta4⁠`

    short.name =

      `⁠beta4⁠`

    output.name =

      `⁠beta4 for GammaJW-Cure⁠`

    output.name.intern =

      `⁠beta4 for GammaJW-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta5'
    hyperid =

      `⁠58204⁠`

    name =

      `⁠beta5⁠`

    short.name =

      `⁠beta5⁠`

    output.name =

      `⁠beta5 for GammaJW-Cure⁠`

    output.name.intern =

      `⁠beta5 for GammaJW-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta6'
    hyperid =

      `⁠58205⁠`

    name =

      `⁠beta6⁠`

    short.name =

      `⁠beta6⁠`

    output.name =

      `⁠beta6 for GammaJW-Cure⁠`

    output.name.intern =

      `⁠beta6 for GammaJW-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta7'
    hyperid =

      `⁠58206⁠`

    name =

      `⁠beta7⁠`

    short.name =

      `⁠beta7⁠`

    output.name =

      `⁠beta7 for GammaJW-Cure⁠`

    output.name.intern =

      `⁠beta7 for GammaJW-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta8'
    hyperid =

      `⁠58207⁠`

    name =

      `⁠beta8⁠`

    short.name =

      `⁠beta8⁠`

    output.name =

      `⁠beta8 for GammaJW-Cure⁠`

    output.name.intern =

      `⁠beta8 for GammaJW-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta9'
    hyperid =

      `⁠58208⁠`

    name =

      `⁠beta9⁠`

    short.name =

      `⁠beta9⁠`

    output.name =

      `⁠beta9 for GammaJW-Cure⁠`

    output.name.intern =

      `⁠beta9 for GammaJW-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta10'
    hyperid =

      `⁠58209⁠`

    name =

      `⁠beta10⁠`

    short.name =

      `⁠beta10⁠`

    output.name =

      `⁠beta10 for GammaJW-Cure⁠`

    output.name.intern =

      `⁠beta10 for GammaJW-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

Model 'gammacount'.
  Properties:
    doc =

      `⁠A Gamma generalisation of the Poisson likelihood⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠FALSE⁠`

    link =

      `⁠default log⁠`

    pdf =

      `⁠gammacount⁠`

  Number of hyperparmeters is 1.

  Hyperparameter 'theta'
    hyperid =

      `⁠59001⁠`

    name =

      `⁠log alpha⁠`

    short.name =

      `⁠alpha⁠`

    output.name =

      `⁠Log-alpha parameter for Gammacount observations⁠`

    output.name.intern =

      `⁠Alpha parameter for Gammacount observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠pc.gammacount⁠`

    param =

      `⁠3⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

Model 'gammacountmean'.
  Properties:
    doc =

      `⁠Another Gamma generalisation of the Poisson likelihood⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠FALSE⁠`

    link =

      `⁠default log⁠`

    pdf =

      `⁠gammacountmean⁠`

  Number of hyperparmeters is 1.

  Hyperparameter 'theta'
    hyperid =

      `⁠59101⁠`

    name =

      `⁠log alpha⁠`

    short.name =

      `⁠alpha⁠`

    output.name =

      `⁠Log-alpha parameter for Gammacountmean observations⁠`

    output.name.intern =

      `⁠Alpha parameter for Gammacountmean observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠pc.gammacount⁠`

    param =

      `⁠3⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

Model 'qkumar'.
  Properties:
    doc =

      `⁠A quantile version of the Kumar likelihood⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠FALSE⁠`

    link =

      `⁠default logit loga cauchit⁠`

    pdf =

      `⁠qkumar⁠`

  Number of hyperparmeters is 1.

  Hyperparameter 'theta'
    hyperid =

      `⁠60001⁠`

    name =

      `⁠precision parameter⁠`

    short.name =

      `⁠prec⁠`

    output.name =

      `⁠precision for qkumar observations⁠`

    output.name.intern =

      `⁠log precision for qkumar observations⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 0.1⁠`

    to.theta =

      `⁠function(x, sc = 0.1) log(x) / sc⁠`

    from.theta =

      `⁠function(x, sc = 0.1) exp(sc * x)⁠`

Model 'qloglogistic'.
  Properties:
    doc =

      `⁠A quantile loglogistic likelihood⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠FALSE⁠`

    link =

      `⁠default log neglog⁠`

    pdf =

      `⁠qloglogistic⁠`

  Number of hyperparmeters is 1.

  Hyperparameter 'theta'
    hyperid =

      `⁠60011⁠`

    name =

      `⁠log alpha⁠`

    short.name =

      `⁠alpha⁠`

    output.name =

      `⁠alpha for qloglogistic observations⁠`

    output.name.intern =

      `⁠log alpha for qloglogistic observations⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠25 25⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

Model 'qloglogisticsurv'.
  Properties:
    doc =

      `⁠A quantile loglogistic likelihood (survival)⁠`

    survival =

      `⁠TRUE⁠`

    discrete =

      `⁠FALSE⁠`

    link =

      `⁠default log neglog⁠`

    pdf =

      `⁠qloglogistic⁠`

  Number of hyperparmeters is 11.

  Hyperparameter 'theta1'
    hyperid =

      `⁠60021⁠`

    name =

      `⁠log alpha⁠`

    short.name =

      `⁠alpha⁠`

    output.name =

      `⁠alpha for qloglogisticsurv observations⁠`

    output.name.intern =

      `⁠log alpha for qloglogisticsurv observations⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠25 25⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠60022⁠`

    name =

      `⁠beta1⁠`

    short.name =

      `⁠beta1⁠`

    output.name =

      `⁠beta1 for qlogLogistic-Cure⁠`

    output.name.intern =

      `⁠beta1 for logLogistic-Cure⁠`

    initial =

      `⁠-5⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠-4 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta3'
    hyperid =

      `⁠60023⁠`

    name =

      `⁠beta2⁠`

    short.name =

      `⁠beta2⁠`

    output.name =

      `⁠beta2 for qlogLogistic-Cure⁠`

    output.name.intern =

      `⁠beta2 for logLogistic-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta4'
    hyperid =

      `⁠60024⁠`

    name =

      `⁠beta3⁠`

    short.name =

      `⁠beta3⁠`

    output.name =

      `⁠beta3 for qlogLogistic-Cure⁠`

    output.name.intern =

      `⁠beta3 for qlogLogistic-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta5'
    hyperid =

      `⁠60025⁠`

    name =

      `⁠beta4⁠`

    short.name =

      `⁠beta4⁠`

    output.name =

      `⁠beta4 for qlogLogistic-Cure⁠`

    output.name.intern =

      `⁠beta4 for qlogLogistic-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta6'
    hyperid =

      `⁠60026⁠`

    name =

      `⁠beta5⁠`

    short.name =

      `⁠beta5⁠`

    output.name =

      `⁠beta5 for qlogLogistic-Cure⁠`

    output.name.intern =

      `⁠beta5 for qlogLogistic-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta7'
    hyperid =

      `⁠60027⁠`

    name =

      `⁠beta6⁠`

    short.name =

      `⁠beta6⁠`

    output.name =

      `⁠beta6 for qlogLogistic-Cure⁠`

    output.name.intern =

      `⁠beta6 for qlogLogistic-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta8'
    hyperid =

      `⁠60028⁠`

    name =

      `⁠beta7⁠`

    short.name =

      `⁠beta7⁠`

    output.name =

      `⁠beta7 for qlogLogistic-Cure⁠`

    output.name.intern =

      `⁠beta7 for qlogLogistic-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta9'
    hyperid =

      `⁠60029⁠`

    name =

      `⁠beta8⁠`

    short.name =

      `⁠beta8⁠`

    output.name =

      `⁠beta8 for qlogLogistic-Cure⁠`

    output.name.intern =

      `⁠beta8 for qlogLogistic-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta10'
    hyperid =

      `⁠60030⁠`

    name =

      `⁠beta9⁠`

    short.name =

      `⁠beta9⁠`

    output.name =

      `⁠beta9 for qlogLogistic-Cure⁠`

    output.name.intern =

      `⁠beta9 for qlogLogistic-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta11'
    hyperid =

      `⁠60031⁠`

    name =

      `⁠beta10⁠`

    short.name =

      `⁠beta10⁠`

    output.name =

      `⁠beta10 for qlogLogistic-Cure⁠`

    output.name.intern =

      `⁠beta10 for qlogLogistic-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

Model 'beta'.
  Properties:
    doc =

      `⁠The Beta likelihood⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠FALSE⁠`

    link =

      `⁠default logit loga cauchit probit cloglog ccloglog loglog⁠`

    pdf =

      `⁠beta⁠`

  Number of hyperparmeters is 1.

  Hyperparameter 'theta'
    hyperid =

      `⁠61001⁠`

    name =

      `⁠precision parameter⁠`

    short.name =

      `⁠phi⁠`

    output.name =

      `⁠precision parameter for the beta observations⁠`

    output.name.intern =

      `⁠intern precision-parameter for the beta observations⁠`

    initial =

      `⁠2.30258509299405⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 0.1⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

Model 'obeta'.
  Properties:
    doc =

      `⁠The ordered Beta likelihood⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠FALSE⁠`

    link =

      `⁠default logit loga cauchit probit cloglog ccloglog loglog⁠`

    pdf =

      `⁠obeta⁠`

  Number of hyperparmeters is 3.

  Hyperparameter 'theta1'
    hyperid =

      `⁠61101⁠`

    name =

      `⁠precision parameter⁠`

    short.name =

      `⁠phi⁠`

    output.name =

      `⁠precision-parameter for the obeta observations⁠`

    output.name.intern =

      `⁠intern precision-parameter for the obeta observations⁠`

    initial =

      `⁠2.30258509299405⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 0.1⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠61102⁠`

    name =

      `⁠offset location⁠`

    short.name =

      `⁠loc⁠`

    output.name =

      `⁠offset location-parameter for the obeta observations⁠`

    output.name.intern =

      `⁠intern offset location-parameter for the obeta observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta3'
    hyperid =

      `⁠61103⁠`

    name =

      `⁠offset width⁠`

    short.name =

      `⁠width⁠`

    output.name =

      `⁠offset width-parameter for the obeta observations⁠`

    output.name.intern =

      `⁠intern offset width-parameter for the obeta observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 1⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

Model 'betabinomial'.
  Properties:
    doc =

      `⁠The Beta-Binomial likelihood⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠TRUE⁠`

    link =

      `⁠default logit loga cauchit probit cloglog ccloglog loglog robit sn⁠`

    pdf =

      `⁠betabinomial⁠`

  Number of hyperparmeters is 1.

  Hyperparameter 'theta'
    hyperid =

      `⁠62001⁠`

    name =

      `⁠overdispersion⁠`

    short.name =

      `⁠rho⁠`

    output.name =

      `⁠overdispersion for the betabinomial observations⁠`

    output.name.intern =

      `⁠intern overdispersion for the betabinomial observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠gaussian⁠`

    param =

      `⁠0 0.4⁠`

    to.theta =

      `⁠function(x) log(x / (1 - x))⁠`

    from.theta =

      `⁠function(x) exp(x) / (1 + exp(x))⁠`

Model 'betabinomialna'.
  Properties:
    doc =

      `⁠The Beta-Binomial Normal approximation likelihood⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠TRUE⁠`

    link =

      `⁠default logit loga cauchit probit cloglog ccloglog loglog robit sn⁠`

    pdf =

      `⁠betabinomialna⁠`

  Number of hyperparmeters is 1.

  Hyperparameter 'theta'
    hyperid =

      `⁠62101⁠`

    name =

      `⁠overdispersion⁠`

    short.name =

      `⁠rho⁠`

    output.name =

      `⁠overdispersion for the betabinomialna observations⁠`

    output.name.intern =

      `⁠intern overdispersion for the betabinomialna observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠gaussian⁠`

    param =

      `⁠0 0.4⁠`

    to.theta =

      `⁠function(x) log(x / (1 - x))⁠`

    from.theta =

      `⁠function(x) exp(x) / (1 + exp(x))⁠`

Model 'cbinomial'.
  Properties:
    doc =

      `⁠The clustered Binomial likelihood⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠TRUE⁠`

    link =

      `⁠default logit loga cauchit probit cloglog ccloglog loglog robit sn⁠`

    pdf =

      `⁠cbinomial⁠`

  Number of hyperparmeters is 0.

Model 'nbinomial'.
  Properties:
    doc =

      `⁠The negBinomial likelihood⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠TRUE⁠`

    link =

      `⁠default log logoffset quantile⁠`

    pdf =

      `⁠nbinomial⁠`

  Number of hyperparmeters is 1.

  Hyperparameter 'theta'
    hyperid =

      `⁠63001⁠`

    name =

      `⁠size⁠`

    short.name =

      `⁠size⁠`

    output.name =

      `⁠size for the nbinomial observations (1/overdispersion)⁠`

    output.name.intern =

      `⁠log size for the nbinomial observations (1/overdispersion)⁠`

    initial =

      `⁠2.30258509299405⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠pc.mgamma⁠`

    param =

      `⁠7⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

Model 'nbinomial2'.
  Properties:
    doc =

      `⁠The negBinomial2 likelihood⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠TRUE⁠`

    link =

      `⁠default logit loga cauchit probit cloglog ccloglog loglog⁠`

    pdf =

      `⁠nbinomial⁠`

  Number of hyperparmeters is 0.

Model 'cennbinomial2'.
  Properties:
    doc =

      `⁠The CenNegBinomial2 likelihood (similar to cenpoisson2)⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠TRUE⁠`

    link =

      `⁠default log logoffset quantile⁠`

    pdf =

      `⁠cennbinomial2⁠`

  Number of hyperparmeters is 1.

  Hyperparameter 'theta'
    hyperid =

      `⁠63101⁠`

    name =

      `⁠size⁠`

    short.name =

      `⁠size⁠`

    output.name =

      `⁠size for the cennbinomial2 observations (1/overdispersion)⁠`

    output.name.intern =

      `⁠log size for the cennbinomial2 observations (1/overdispersion)⁠`

    initial =

      `⁠2.30258509299405⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠pc.mgamma⁠`

    param =

      `⁠7⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

Model 'simplex'.
  Properties:
    doc =

      `⁠The simplex likelihood⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠FALSE⁠`

    link =

      `⁠default logit loga cauchit probit cloglog ccloglog loglog⁠`

    pdf =

      `⁠simplex⁠`

  Number of hyperparmeters is 1.

  Hyperparameter 'theta'
    hyperid =

      `⁠64001⁠`

    name =

      `⁠log precision⁠`

    short.name =

      `⁠prec⁠`

    output.name =

      `⁠Precision for the Simplex observations⁠`

    output.name.intern =

      `⁠Log precision for the Simplex observations⁠`

    initial =

      `⁠4⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 5e-05⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

Model 'gaussian'.
  Properties:
    doc =

      `⁠The Gaussian likelihoood⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠FALSE⁠`

    link =

      `⁠default identity logit loga cauchit log logoffset⁠`

    pdf =

      `⁠gaussian⁠`

  Number of hyperparmeters is 2.

  Hyperparameter 'theta1'
    hyperid =

      `⁠65001⁠`

    name =

      `⁠log precision⁠`

    short.name =

      `⁠prec⁠`

    output.name =

      `⁠Precision for the Gaussian observations⁠`

    output.name.intern =

      `⁠Log precision for the Gaussian observations⁠`

    initial =

      `⁠4⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 5e-05⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠65002⁠`

    name =

      `⁠log precision offset⁠`

    short.name =

      `⁠precoffset⁠`

    output.name =

      `⁠NOT IN USE⁠`

    output.name.intern =

      `⁠NOT IN USE⁠`

    initial =

      `⁠72.0873067782343⁠`

    fixed =

      `⁠TRUE⁠`

    prior =

      `⁠none⁠`

    param =

      `⁠⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

Model 'stdgaussian'.
  Properties:
    doc =

      `⁠The stdGaussian likelihoood⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠FALSE⁠`

    link =

      `⁠default identity logit loga cauchit log logoffset⁠`

    pdf =

      `⁠gaussian⁠`

  Number of hyperparmeters is 0.

Model 'gaussianjw'.
  Properties:
    doc =

      `⁠The GaussianJW likelihoood⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠FALSE⁠`

    link =

      `⁠default logit probit⁠`

    pdf =

      `⁠gaussianjw⁠`

  Number of hyperparmeters is 3.

  Hyperparameter 'theta1'
    hyperid =

      `⁠65101⁠`

    name =

      `⁠beta1⁠`

    short.name =

      `⁠beta1⁠`

    output.name =

      `⁠beta1 for GaussianJW observations⁠`

    output.name.intern =

      `⁠beta1 for GaussianJW observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠65102⁠`

    name =

      `⁠beta2⁠`

    short.name =

      `⁠beta2⁠`

    output.name =

      `⁠beta2 for GaussianJW observations⁠`

    output.name.intern =

      `⁠beta2 for GaussianJW observations⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta3'
    hyperid =

      `⁠65103⁠`

    name =

      `⁠beta3⁠`

    short.name =

      `⁠beta3⁠`

    output.name =

      `⁠beta3 for GaussianJW observations⁠`

    output.name.intern =

      `⁠beta3 for GaussianJW observations⁠`

    initial =

      `⁠-1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠-1 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

Model 'agaussian'.
  Properties:
    doc =

      `⁠The aggregated Gaussian likelihoood⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠FALSE⁠`

    link =

      `⁠default identity logit loga cauchit log logoffset⁠`

    pdf =

      `⁠agaussian⁠`

  Number of hyperparmeters is 1.

  Hyperparameter 'theta'
    hyperid =

      `⁠66001⁠`

    name =

      `⁠log precision⁠`

    short.name =

      `⁠prec⁠`

    output.name =

      `⁠Precision for the AggGaussian observations⁠`

    output.name.intern =

      `⁠Log precision for the AggGaussian observations⁠`

    initial =

      `⁠4⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 5e-05⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

Model 'ggaussian'.
  Properties:
    doc =

      `⁠Generalized Gaussian⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠FALSE⁠`

    link =

      `⁠default identity⁠`

    link.simple =

      `⁠default log⁠`

    pdf =

      `⁠ggaussian⁠`

  Number of hyperparmeters is 10.

  Hyperparameter 'theta1'
    hyperid =

      `⁠66501⁠`

    name =

      `⁠beta1⁠`

    short.name =

      `⁠beta1⁠`

    output.name =

      `⁠beta1 for ggaussian observations⁠`

    output.name.intern =

      `⁠beta1 for ggaussian observations⁠`

    initial =

      `⁠4⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠9.33 0.61⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠66502⁠`

    name =

      `⁠beta2⁠`

    short.name =

      `⁠beta2⁠`

    output.name =

      `⁠beta2 for ggaussian observations⁠`

    output.name.intern =

      `⁠beta2 for ggaussian observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta3'
    hyperid =

      `⁠66503⁠`

    name =

      `⁠beta3⁠`

    short.name =

      `⁠beta3⁠`

    output.name =

      `⁠beta3 for ggaussian observations⁠`

    output.name.intern =

      `⁠beta3 for ggaussian observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta4'
    hyperid =

      `⁠66504⁠`

    name =

      `⁠beta4⁠`

    short.name =

      `⁠beta4⁠`

    output.name =

      `⁠beta4 for ggaussian observations⁠`

    output.name.intern =

      `⁠beta4 for ggaussian observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta5'
    hyperid =

      `⁠66505⁠`

    name =

      `⁠beta5⁠`

    short.name =

      `⁠beta5⁠`

    output.name =

      `⁠beta5 for ggaussian observations⁠`

    output.name.intern =

      `⁠beta5 for ggaussian observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta6'
    hyperid =

      `⁠66506⁠`

    name =

      `⁠beta6⁠`

    short.name =

      `⁠beta6⁠`

    output.name =

      `⁠beta6 for ggaussian observations⁠`

    output.name.intern =

      `⁠beta6 for ggaussian observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta7'
    hyperid =

      `⁠66507⁠`

    name =

      `⁠beta7⁠`

    short.name =

      `⁠beta7⁠`

    output.name =

      `⁠beta7 for ggaussian observations⁠`

    output.name.intern =

      `⁠beta7 for ggaussian observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta8'
    hyperid =

      `⁠66508⁠`

    name =

      `⁠beta8⁠`

    short.name =

      `⁠beta8⁠`

    output.name =

      `⁠beta8 for ggaussian observations⁠`

    output.name.intern =

      `⁠beta8 for ggaussian observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta9'
    hyperid =

      `⁠66509⁠`

    name =

      `⁠beta9⁠`

    short.name =

      `⁠beta9⁠`

    output.name =

      `⁠beta9 for ggaussian observations⁠`

    output.name.intern =

      `⁠beta9 for ggaussian observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta10'
    hyperid =

      `⁠66510⁠`

    name =

      `⁠beta10⁠`

    short.name =

      `⁠beta10⁠`

    output.name =

      `⁠beta10 for ggaussian observations⁠`

    output.name.intern =

      `⁠beta10 for ggaussian observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

Model 'ggaussianS'.
  Properties:
    doc =

      `⁠Generalized GaussianS⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠FALSE⁠`

    link =

      `⁠default log⁠`

    link.simple =

      `⁠default identity⁠`

    pdf =

      `⁠ggaussian⁠`

  Number of hyperparmeters is 10.

  Hyperparameter 'theta1'
    hyperid =

      `⁠66601⁠`

    name =

      `⁠beta1⁠`

    short.name =

      `⁠beta1⁠`

    output.name =

      `⁠beta1 for ggaussianS observations⁠`

    output.name.intern =

      `⁠beta1 for ggaussianS observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 0.001⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠66602⁠`

    name =

      `⁠beta2⁠`

    short.name =

      `⁠beta2⁠`

    output.name =

      `⁠beta2 for ggaussianS observations⁠`

    output.name.intern =

      `⁠beta2 for ggaussianS observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 0.001⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta3'
    hyperid =

      `⁠66603⁠`

    name =

      `⁠beta3⁠`

    short.name =

      `⁠beta3⁠`

    output.name =

      `⁠beta3 for ggaussianS observations⁠`

    output.name.intern =

      `⁠beta3 for ggaussianS observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 0.001⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta4'
    hyperid =

      `⁠66604⁠`

    name =

      `⁠beta4⁠`

    short.name =

      `⁠beta4⁠`

    output.name =

      `⁠beta4 for ggaussianS observations⁠`

    output.name.intern =

      `⁠beta4 for ggaussianS observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 0.001⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta5'
    hyperid =

      `⁠66605⁠`

    name =

      `⁠beta5⁠`

    short.name =

      `⁠beta5⁠`

    output.name =

      `⁠beta5 for ggaussianS observations⁠`

    output.name.intern =

      `⁠beta5 for ggaussianS observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 0.001⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta6'
    hyperid =

      `⁠66606⁠`

    name =

      `⁠beta6⁠`

    short.name =

      `⁠beta6⁠`

    output.name =

      `⁠beta6 for ggaussianS observations⁠`

    output.name.intern =

      `⁠beta6 for ggaussianS observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 0.001⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta7'
    hyperid =

      `⁠66607⁠`

    name =

      `⁠beta7⁠`

    short.name =

      `⁠beta7⁠`

    output.name =

      `⁠beta7 for ggaussianS observations⁠`

    output.name.intern =

      `⁠beta7 for ggaussianS observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 0.001⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta8'
    hyperid =

      `⁠66608⁠`

    name =

      `⁠beta8⁠`

    short.name =

      `⁠beta8⁠`

    output.name =

      `⁠beta8 for ggaussianS observations⁠`

    output.name.intern =

      `⁠beta8 for ggaussianS observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 0.001⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta9'
    hyperid =

      `⁠66609⁠`

    name =

      `⁠beta9⁠`

    short.name =

      `⁠beta9⁠`

    output.name =

      `⁠beta9 for ggaussianS observations⁠`

    output.name.intern =

      `⁠beta9 for ggaussianS observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 0.001⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta10'
    hyperid =

      `⁠66610⁠`

    name =

      `⁠beta10⁠`

    short.name =

      `⁠beta10⁠`

    output.name =

      `⁠beta10 for ggaussianS observations⁠`

    output.name.intern =

      `⁠beta10 for ggaussianS observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 0.001⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

Model 'bcgaussian'.
  Properties:
    doc =

      `⁠The Box-Cox Gaussian likelihoood⁠`

    status =

      `⁠disabled⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠FALSE⁠`

    link =

      `⁠default identity⁠`

    pdf =

      `⁠bcgaussian⁠`

  Number of hyperparmeters is 2.

  Hyperparameter 'theta1'
    hyperid =

      `⁠65010⁠`

    name =

      `⁠log precision⁠`

    short.name =

      `⁠prec⁠`

    output.name =

      `⁠Precision for the Box-Cox Gaussian observations⁠`

    output.name.intern =

      `⁠Log precision for the Box-Cox Gaussian observations⁠`

    initial =

      `⁠4⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 5e-05⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠65011⁠`

    name =

      `⁠Box-Cox transformation parameter⁠`

    short.name =

      `⁠lambda⁠`

    output.name =

      `⁠NOT IN USE⁠`

    output.name.intern =

      `⁠NOT IN USE⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠gaussian⁠`

    param =

      `⁠1 8⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

Model 'exppower'.
  Properties:
    doc =

      `⁠The exponential power likelihoood⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠FALSE⁠`

    link =

      `⁠default identity quantile⁠`

    pdf =

      `⁠exppower⁠`

  Number of hyperparmeters is 2.

  Hyperparameter 'theta1'
    hyperid =

      `⁠65021⁠`

    name =

      `⁠log precision⁠`

    short.name =

      `⁠prec⁠`

    output.name =

      `⁠NOT IN USE⁠`

    output.name.intern =

      `⁠NOT IN USE⁠`

    initial =

      `⁠4⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 5e-05⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠65022⁠`

    name =

      `⁠power⁠`

    short.name =

      `⁠beta⁠`

    output.name =

      `⁠NOT IN USE⁠`

    output.name.intern =

      `⁠NOT IN USE⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠gaussian⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) log(x-1)⁠`

    from.theta =

      `⁠function(x) 1+exp(x)⁠`

Model 'sem'.
  Properties:
    doc =

      `⁠The SEM likelihoood⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠FALSE⁠`

    link =

      `⁠default identity⁠`

    pdf =

      `⁠sem⁠`

  Number of hyperparmeters is 0.

Model 'rcpoisson'.
  Properties:
    doc =

      `⁠Randomly censored Poisson⁠`

    status =

      `⁠experimental⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠TRUE⁠`

    link =

      `⁠default log⁠`

    pdf =

      `⁠rcpoisson⁠`

  Number of hyperparmeters is 10.

  Hyperparameter 'theta1'
    hyperid =

      `⁠66701⁠`

    name =

      `⁠beta1⁠`

    short.name =

      `⁠beta1⁠`

    output.name =

      `⁠beta1 rcpoisson observations⁠`

    output.name.intern =

      `⁠beta1 rcpoisson observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠66702⁠`

    name =

      `⁠beta2⁠`

    short.name =

      `⁠beta2⁠`

    output.name =

      `⁠beta2 rcpoisson observations⁠`

    output.name.intern =

      `⁠beta2 rcpoisson observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta3'
    hyperid =

      `⁠66703⁠`

    name =

      `⁠beta3⁠`

    short.name =

      `⁠beta3⁠`

    output.name =

      `⁠beta3 rcpoisson observations⁠`

    output.name.intern =

      `⁠beta3 rcpoisson observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta4'
    hyperid =

      `⁠66704⁠`

    name =

      `⁠beta4⁠`

    short.name =

      `⁠beta4⁠`

    output.name =

      `⁠beta4 rcpoisson observations⁠`

    output.name.intern =

      `⁠beta4 rcpoisson observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta5'
    hyperid =

      `⁠66705⁠`

    name =

      `⁠beta5⁠`

    short.name =

      `⁠beta5⁠`

    output.name =

      `⁠beta5 rcpoisson observations⁠`

    output.name.intern =

      `⁠beta5 rcpoisson observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta6'
    hyperid =

      `⁠66706⁠`

    name =

      `⁠beta6⁠`

    short.name =

      `⁠beta6⁠`

    output.name =

      `⁠beta6 rcpoisson observations⁠`

    output.name.intern =

      `⁠beta6 rcpoisson observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta7'
    hyperid =

      `⁠66707⁠`

    name =

      `⁠beta7⁠`

    short.name =

      `⁠beta7⁠`

    output.name =

      `⁠beta7 rcpoisson observations⁠`

    output.name.intern =

      `⁠beta7 rcpoisson observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta8'
    hyperid =

      `⁠66708⁠`

    name =

      `⁠beta8⁠`

    short.name =

      `⁠beta8⁠`

    output.name =

      `⁠beta8 rcpoisson observations⁠`

    output.name.intern =

      `⁠beta8 rcpoisson observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta9'
    hyperid =

      `⁠66709⁠`

    name =

      `⁠beta9⁠`

    short.name =

      `⁠beta9⁠`

    output.name =

      `⁠beta9 rcpoisson observations⁠`

    output.name.intern =

      `⁠beta9 rcpoisson observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta10'
    hyperid =

      `⁠66710⁠`

    name =

      `⁠beta10⁠`

    short.name =

      `⁠beta10⁠`

    output.name =

      `⁠beta10 rcpoisson observations⁠`

    output.name.intern =

      `⁠beta10 rcpoisson observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

Model 'tpoisson'.
  Properties:
    doc =

      `⁠Thinned Poisson⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠TRUE⁠`

    link =

      `⁠default log⁠`

    pdf =

      `⁠tpoisson⁠`

  Number of hyperparmeters is 10.

  Hyperparameter 'theta1'
    hyperid =

      `⁠66721⁠`

    name =

      `⁠beta1⁠`

    short.name =

      `⁠beta1⁠`

    output.name =

      `⁠beta1 tpoisson observations⁠`

    output.name.intern =

      `⁠beta1 tpoisson observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠66722⁠`

    name =

      `⁠beta2⁠`

    short.name =

      `⁠beta2⁠`

    output.name =

      `⁠beta2 tpoisson observations⁠`

    output.name.intern =

      `⁠beta2 tpoisson observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta3'
    hyperid =

      `⁠66723⁠`

    name =

      `⁠beta3⁠`

    short.name =

      `⁠beta3⁠`

    output.name =

      `⁠beta3 tpoisson observations⁠`

    output.name.intern =

      `⁠beta3 tpoisson observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta4'
    hyperid =

      `⁠66724⁠`

    name =

      `⁠beta4⁠`

    short.name =

      `⁠beta4⁠`

    output.name =

      `⁠beta4 tpoisson observations⁠`

    output.name.intern =

      `⁠beta4 tpoisson observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta5'
    hyperid =

      `⁠66725⁠`

    name =

      `⁠beta5⁠`

    short.name =

      `⁠beta5⁠`

    output.name =

      `⁠beta5 tpoisson observations⁠`

    output.name.intern =

      `⁠beta5 tpoisson observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta6'
    hyperid =

      `⁠66726⁠`

    name =

      `⁠beta6⁠`

    short.name =

      `⁠beta6⁠`

    output.name =

      `⁠beta6 tpoisson observations⁠`

    output.name.intern =

      `⁠beta6 tpoisson observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta7'
    hyperid =

      `⁠66727⁠`

    name =

      `⁠beta7⁠`

    short.name =

      `⁠beta7⁠`

    output.name =

      `⁠beta7 tpoisson observations⁠`

    output.name.intern =

      `⁠beta7 tpoisson observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta8'
    hyperid =

      `⁠66728⁠`

    name =

      `⁠beta8⁠`

    short.name =

      `⁠beta8⁠`

    output.name =

      `⁠beta8 tpoisson observations⁠`

    output.name.intern =

      `⁠beta8 tpoisson observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta9'
    hyperid =

      `⁠66729⁠`

    name =

      `⁠beta9⁠`

    short.name =

      `⁠beta9⁠`

    output.name =

      `⁠beta9 tpoisson observations⁠`

    output.name.intern =

      `⁠beta9 tpoisson observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta10'
    hyperid =

      `⁠66730⁠`

    name =

      `⁠beta10⁠`

    short.name =

      `⁠beta10⁠`

    output.name =

      `⁠beta10 tpoisson observations⁠`

    output.name.intern =

      `⁠beta10 tpoisson observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

Model 'circularnormal'.
  Properties:
    doc =

      `⁠The circular Gaussian likelihoood⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠FALSE⁠`

    link =

      `⁠default tan tan.pi⁠`

    pdf =

      `⁠circular-normal⁠`

    status =

      `⁠disabled⁠`

  Number of hyperparmeters is 1.

  Hyperparameter 'theta'
    hyperid =

      `⁠67001⁠`

    name =

      `⁠log precision parameter⁠`

    short.name =

      `⁠prec⁠`

    output.name =

      `⁠Precision parameter for the Circular Normal observations⁠`

    output.name.intern =

      `⁠Log precision parameter for the Circular Normal observations⁠`

    initial =

      `⁠2⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 0.01⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

Model 'wrappedcauchy'.
  Properties:
    doc =

      `⁠The wrapped Cauchy likelihoood⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠FALSE⁠`

    link =

      `⁠default tan tan.pi⁠`

    pdf =

      `⁠wrapped-cauchy⁠`

    status =

      `⁠disabled⁠`

  Number of hyperparmeters is 1.

  Hyperparameter 'theta'
    hyperid =

      `⁠68001⁠`

    name =

      `⁠log precision parameter⁠`

    short.name =

      `⁠prec⁠`

    output.name =

      `⁠Precision parameter for the Wrapped Cauchy observations⁠`

    output.name.intern =

      `⁠Log precision parameter for the Wrapped Cauchy observations⁠`

    initial =

      `⁠2⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 0.005⁠`

    to.theta =

      `⁠function(x) log(x / (1 - x))⁠`

    from.theta =

      `⁠function(x) exp(x) / (1 + exp(x))⁠`

Model 'iidgamma'.
  Properties:
    doc =

      `⁠(experimental)⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠FALSE⁠`

    link =

      `⁠default identity⁠`

    pdf =

      `⁠iidgamma⁠`

  Number of hyperparmeters is 2.

  Hyperparameter 'theta1'
    hyperid =

      `⁠69001⁠`

    name =

      `⁠logshape⁠`

    short.name =

      `⁠shape⁠`

    output.name =

      `⁠Shape parameter for iid-gamma⁠`

    output.name.intern =

      `⁠Log shape parameter for iid-gamma⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠100 100⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠69002⁠`

    name =

      `⁠lograte⁠`

    short.name =

      `⁠rate⁠`

    output.name =

      `⁠Rate parameter for iid-gamma⁠`

    output.name.intern =

      `⁠Log rate parameter for iid-gamma⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠100 100⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

Model 'iidlogitbeta'.
  Properties:
    doc =

      `⁠(experimental)⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠FALSE⁠`

    link =

      `⁠default logit loga⁠`

    pdf =

      `⁠iidlogitbeta⁠`

  Number of hyperparmeters is 2.

  Hyperparameter 'theta1'
    hyperid =

      `⁠70001⁠`

    name =

      `⁠log.a⁠`

    short.name =

      `⁠a⁠`

    output.name =

      `⁠a parameter for iid-beta⁠`

    output.name.intern =

      `⁠Log a parameter for iid-beta⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 1⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠70002⁠`

    name =

      `⁠log.b⁠`

    short.name =

      `⁠b⁠`

    output.name =

      `⁠Rate parameter for iid-gamma⁠`

    output.name.intern =

      `⁠Log rate parameter for iid-gamma⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 1⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

Model 'loggammafrailty'.
  Properties:
    doc =

      `⁠(experimental)⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠FALSE⁠`

    link =

      `⁠default identity⁠`

    pdf =

      `⁠loggammafrailty⁠`

  Number of hyperparmeters is 1.

  Hyperparameter 'theta'
    hyperid =

      `⁠71001⁠`

    name =

      `⁠log precision⁠`

    short.name =

      `⁠prec⁠`

    output.name =

      `⁠precision for the gamma frailty⁠`

    output.name.intern =

      `⁠log precision for the gamma frailty⁠`

    initial =

      `⁠4⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 5e-05⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

Model 'logistic'.
  Properties:
    doc =

      `⁠The Logistic likelihoood⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠FALSE⁠`

    link =

      `⁠default identity⁠`

    pdf =

      `⁠logistic⁠`

  Number of hyperparmeters is 1.

  Hyperparameter 'theta'
    hyperid =

      `⁠72001⁠`

    name =

      `⁠log precision⁠`

    short.name =

      `⁠prec⁠`

    output.name =

      `⁠precision for the logistic observations⁠`

    output.name.intern =

      `⁠log precision for the logistic observations⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 5e-05⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

Model 'sn'.
  Properties:
    doc =

      `⁠The Skew-Normal likelihoood⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠FALSE⁠`

    link =

      `⁠default identity⁠`

    pdf =

      `⁠sn⁠`

  Number of hyperparmeters is 2.

  Hyperparameter 'theta1'
    hyperid =

      `⁠74001⁠`

    name =

      `⁠log precision⁠`

    short.name =

      `⁠prec⁠`

    output.name =

      `⁠precision for skew-normal observations⁠`

    output.name.intern =

      `⁠log precision for skew-normal observations⁠`

    initial =

      `⁠4⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 5e-05⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠74002⁠`

    name =

      `⁠logit skew⁠`

    short.name =

      `⁠skew⁠`

    output.name =

      `⁠Skewness for skew-normal observations⁠`

    output.name.intern =

      `⁠Intern skewness for skew-normal observations⁠`

    initial =

      `⁠0.00123456789⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠pc.sn⁠`

    param =

      `⁠10⁠`

    to.theta =

      `⁠function(x, skew.max = 0.988) log((1 + x / skew.max) / (1 - x / skew.max))⁠`

    from.theta =

      `⁠function(x, skew.max = 0.988) skew.max * (2 * exp(x) / (1 + exp(x)) - 1)⁠`

Model 'gev'.
  Properties:
    doc =

      `⁠The Generalized Extreme Value likelihood⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠FALSE⁠`

    link =

      `⁠default identity⁠`

    status =

      `⁠disabled: Use likelihood model 'bgev' instead; see inla.doc('bgev')⁠`

    pdf =

      `⁠gev⁠`

  Number of hyperparmeters is 2.

  Hyperparameter 'theta1'
    hyperid =

      `⁠76001⁠`

    name =

      `⁠log precision⁠`

    short.name =

      `⁠prec⁠`

    output.name =

      `⁠precision for GEV observations⁠`

    output.name.intern =

      `⁠log precision for GEV observations⁠`

    initial =

      `⁠4⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 5e-05⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠76002⁠`

    name =

      `⁠tail parameter⁠`

    short.name =

      `⁠tail⁠`

    output.name =

      `⁠tail parameter for GEV observations⁠`

    output.name.intern =

      `⁠tail parameter for GEV observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠gaussian⁠`

    param =

      `⁠0 25⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

Model 'lognormal'.
  Properties:
    doc =

      `⁠The log-Normal likelihood⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠FALSE⁠`

    link =

      `⁠default identity⁠`

    pdf =

      `⁠lognormal⁠`

  Number of hyperparmeters is 1.

  Hyperparameter 'theta'
    hyperid =

      `⁠77101⁠`

    name =

      `⁠log precision⁠`

    short.name =

      `⁠prec⁠`

    output.name =

      `⁠Precision for the lognormal observations⁠`

    output.name.intern =

      `⁠Log precision for the lognormal observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 5e-05⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

Model 'lognormalsurv'.
  Properties:
    doc =

      `⁠The log-Normal likelihood (survival)⁠`

    survival =

      `⁠TRUE⁠`

    discrete =

      `⁠FALSE⁠`

    link =

      `⁠default identity⁠`

    pdf =

      `⁠lognormal⁠`

  Number of hyperparmeters is 11.

  Hyperparameter 'theta1'
    hyperid =

      `⁠78001⁠`

    name =

      `⁠log precision⁠`

    short.name =

      `⁠prec⁠`

    output.name =

      `⁠Precision for the lognormalsurv observations⁠`

    output.name.intern =

      `⁠Log precision for the lognormalsurv observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 5e-05⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠78002⁠`

    name =

      `⁠beta1⁠`

    short.name =

      `⁠beta1⁠`

    output.name =

      `⁠beta1 for logNormal-Cure⁠`

    output.name.intern =

      `⁠beta1 for logNormal-Cure⁠`

    initial =

      `⁠-7⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠-4 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta3'
    hyperid =

      `⁠78003⁠`

    name =

      `⁠beta2⁠`

    short.name =

      `⁠beta2⁠`

    output.name =

      `⁠beta2 for logNormal-Cure⁠`

    output.name.intern =

      `⁠beta2 for logNormal-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta4'
    hyperid =

      `⁠78004⁠`

    name =

      `⁠beta3⁠`

    short.name =

      `⁠beta3⁠`

    output.name =

      `⁠beta3 for logNormal-Cure⁠`

    output.name.intern =

      `⁠beta3 for logNormal-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta5'
    hyperid =

      `⁠78005⁠`

    name =

      `⁠beta4⁠`

    short.name =

      `⁠beta4⁠`

    output.name =

      `⁠beta4 for logNormal-Cure⁠`

    output.name.intern =

      `⁠beta4 for logNormal-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta6'
    hyperid =

      `⁠78006⁠`

    name =

      `⁠beta5⁠`

    short.name =

      `⁠beta5⁠`

    output.name =

      `⁠beta5 for logNormal-Cure⁠`

    output.name.intern =

      `⁠beta5 for logNormal-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta7'
    hyperid =

      `⁠78007⁠`

    name =

      `⁠beta6⁠`

    short.name =

      `⁠beta6⁠`

    output.name =

      `⁠beta6 for logNormal-Cure⁠`

    output.name.intern =

      `⁠beta6 for logNormal-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta8'
    hyperid =

      `⁠78008⁠`

    name =

      `⁠beta7⁠`

    short.name =

      `⁠beta7⁠`

    output.name =

      `⁠beta7 for logNormal-Cure⁠`

    output.name.intern =

      `⁠beta7 for logNormal-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta9'
    hyperid =

      `⁠78009⁠`

    name =

      `⁠beta8⁠`

    short.name =

      `⁠beta8⁠`

    output.name =

      `⁠beta8 for logNormal-Cure⁠`

    output.name.intern =

      `⁠beta8 for logNormal-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta10'
    hyperid =

      `⁠78010⁠`

    name =

      `⁠beta9⁠`

    short.name =

      `⁠beta9⁠`

    output.name =

      `⁠beta9 for logNormal-Cure⁠`

    output.name.intern =

      `⁠beta9 for logNormal-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta11'
    hyperid =

      `⁠78011⁠`

    name =

      `⁠beta10⁠`

    short.name =

      `⁠beta10⁠`

    output.name =

      `⁠beta10 for logNormal-Cure⁠`

    output.name.intern =

      `⁠beta10 for logNormal-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

Model 'exponential'.
  Properties:
    doc =

      `⁠The Exponential likelihood⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠FALSE⁠`

    link =

      `⁠default log⁠`

    pdf =

      `⁠exponential⁠`

  Number of hyperparmeters is 0.

Model 'exponentialsurv'.
  Properties:
    doc =

      `⁠The Exponential likelihood (survival)⁠`

    survival =

      `⁠TRUE⁠`

    discrete =

      `⁠FALSE⁠`

    link =

      `⁠default log neglog⁠`

    pdf =

      `⁠exponential⁠`

  Number of hyperparmeters is 10.

  Hyperparameter 'theta1'
    hyperid =

      `⁠78020⁠`

    name =

      `⁠beta1⁠`

    short.name =

      `⁠beta1⁠`

    output.name =

      `⁠beta1 for Exp-Cure⁠`

    output.name.intern =

      `⁠beta1 for Exp-Cure⁠`

    initial =

      `⁠-4⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠-1 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠78021⁠`

    name =

      `⁠beta2⁠`

    short.name =

      `⁠beta2⁠`

    output.name =

      `⁠beta2 for Exp-Cure⁠`

    output.name.intern =

      `⁠beta2 for Exp-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta3'
    hyperid =

      `⁠78022⁠`

    name =

      `⁠beta3⁠`

    short.name =

      `⁠beta3⁠`

    output.name =

      `⁠beta3 for Exp-Cure⁠`

    output.name.intern =

      `⁠beta3 for Exp-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta4'
    hyperid =

      `⁠78023⁠`

    name =

      `⁠beta4⁠`

    short.name =

      `⁠beta4⁠`

    output.name =

      `⁠beta4 for Exp-Cure⁠`

    output.name.intern =

      `⁠beta4 for Exp-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta5'
    hyperid =

      `⁠78024⁠`

    name =

      `⁠beta5⁠`

    short.name =

      `⁠beta5⁠`

    output.name =

      `⁠beta5 for Exp-Cure⁠`

    output.name.intern =

      `⁠beta5 for Exp-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta6'
    hyperid =

      `⁠78025⁠`

    name =

      `⁠beta6⁠`

    short.name =

      `⁠beta6⁠`

    output.name =

      `⁠beta6 for Exp-Cure⁠`

    output.name.intern =

      `⁠beta6 for Exp-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta7'
    hyperid =

      `⁠78026⁠`

    name =

      `⁠beta7⁠`

    short.name =

      `⁠beta7⁠`

    output.name =

      `⁠beta7 for Exp-Cure⁠`

    output.name.intern =

      `⁠beta7 for Exp-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta8'
    hyperid =

      `⁠78027⁠`

    name =

      `⁠beta8⁠`

    short.name =

      `⁠beta8⁠`

    output.name =

      `⁠beta8 for Exp-Cure⁠`

    output.name.intern =

      `⁠beta8 for Exp-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta9'
    hyperid =

      `⁠78028⁠`

    name =

      `⁠beta9⁠`

    short.name =

      `⁠beta9⁠`

    output.name =

      `⁠beta9 for Exp-Cure⁠`

    output.name.intern =

      `⁠beta9 for Exp-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta10'
    hyperid =

      `⁠78029⁠`

    name =

      `⁠beta10⁠`

    short.name =

      `⁠beta10⁠`

    output.name =

      `⁠beta10 for Exp-Cure⁠`

    output.name.intern =

      `⁠beta10 for Exp-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

Model 'coxph'.
  Properties:
    doc =

      `⁠Cox-proportional hazard likelihood⁠`

    survival =

      `⁠TRUE⁠`

    discrete =

      `⁠TRUE⁠`

    link =

      `⁠default log neglog⁠`

    pdf =

      `⁠coxph⁠`

  Number of hyperparmeters is 0.

Model 'weibull'.
  Properties:
    doc =

      `⁠The Weibull likelihood⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠FALSE⁠`

    link =

      `⁠default log neglog quantile⁠`

    pdf =

      `⁠weibull⁠`

  Number of hyperparmeters is 1.

  Hyperparameter 'theta'
    hyperid =

      `⁠79001⁠`

    name =

      `⁠log alpha⁠`

    short.name =

      `⁠alpha⁠`

    output.name =

      `⁠alpha parameter for weibull⁠`

    output.name.intern =

      `⁠alpha_intern for weibull⁠`

    initial =

      `⁠-2⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠pc.alphaw⁠`

    param =

      `⁠5⁠`

    to.theta =

      `⁠function(x, sc = 0.1) log(x) / sc⁠`

    from.theta =

      `⁠function(x, sc = 0.1) exp(sc * x)⁠`

Model 'weibullsurv'.
  Properties:
    doc =

      `⁠The Weibull likelihood (survival)⁠`

    survival =

      `⁠TRUE⁠`

    discrete =

      `⁠FALSE⁠`

    link =

      `⁠default log neglog quantile⁠`

    pdf =

      `⁠weibull⁠`

  Number of hyperparmeters is 11.

  Hyperparameter 'theta'
    hyperid =

      `⁠79101⁠`

    name =

      `⁠log alpha⁠`

    short.name =

      `⁠alpha⁠`

    output.name =

      `⁠alpha parameter for weibullsurv⁠`

    output.name.intern =

      `⁠alpha_intern for weibullsurv⁠`

    initial =

      `⁠-2⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠pc.alphaw⁠`

    param =

      `⁠5⁠`

    to.theta =

      `⁠function(x, sc = 0.1) log(x) / sc⁠`

    from.theta =

      `⁠function(x, sc = 0.1) exp(sc * x)⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠79102⁠`

    name =

      `⁠beta1⁠`

    short.name =

      `⁠beta1⁠`

    output.name =

      `⁠beta1 for Weibull-Cure⁠`

    output.name.intern =

      `⁠beta1 for Weibull-Cure⁠`

    initial =

      `⁠-7⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠-4 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta3'
    hyperid =

      `⁠79103⁠`

    name =

      `⁠beta2⁠`

    short.name =

      `⁠beta2⁠`

    output.name =

      `⁠beta2 for Weibull-Cure⁠`

    output.name.intern =

      `⁠beta2 for Weibull-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta4'
    hyperid =

      `⁠79104⁠`

    name =

      `⁠beta3⁠`

    short.name =

      `⁠beta3⁠`

    output.name =

      `⁠beta3 for Weibull-Cure⁠`

    output.name.intern =

      `⁠beta3 for Weibull-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta5'
    hyperid =

      `⁠79105⁠`

    name =

      `⁠beta4⁠`

    short.name =

      `⁠beta4⁠`

    output.name =

      `⁠beta4 for Weibull-Cure⁠`

    output.name.intern =

      `⁠beta4 for Weibull-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta6'
    hyperid =

      `⁠79106⁠`

    name =

      `⁠beta5⁠`

    short.name =

      `⁠beta5⁠`

    output.name =

      `⁠beta5 for Weibull-Cure⁠`

    output.name.intern =

      `⁠beta5 for Weibull-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta7'
    hyperid =

      `⁠79107⁠`

    name =

      `⁠beta6⁠`

    short.name =

      `⁠beta6⁠`

    output.name =

      `⁠beta6 for Weibull-Cure⁠`

    output.name.intern =

      `⁠beta6 for Weibull-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta8'
    hyperid =

      `⁠79108⁠`

    name =

      `⁠beta7⁠`

    short.name =

      `⁠beta7⁠`

    output.name =

      `⁠beta7 for Weibull-Cure⁠`

    output.name.intern =

      `⁠beta7 for Weibull-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta9'
    hyperid =

      `⁠79109⁠`

    name =

      `⁠beta8⁠`

    short.name =

      `⁠beta8⁠`

    output.name =

      `⁠beta8 for Weibull-Cure⁠`

    output.name.intern =

      `⁠beta8 for Weibull-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta10'
    hyperid =

      `⁠79110⁠`

    name =

      `⁠beta9⁠`

    short.name =

      `⁠beta9⁠`

    output.name =

      `⁠beta9 for Weibull-Cure⁠`

    output.name.intern =

      `⁠beta9 for Weibull-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta11'
    hyperid =

      `⁠79111⁠`

    name =

      `⁠beta10⁠`

    short.name =

      `⁠beta10⁠`

    output.name =

      `⁠beta10 for Weibull-Cure⁠`

    output.name.intern =

      `⁠beta10 for Weibull-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

Model 'loglogistic'.
  Properties:
    doc =

      `⁠The loglogistic likelihood⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠FALSE⁠`

    link =

      `⁠default log neglog⁠`

    pdf =

      `⁠loglogistic⁠`

  Number of hyperparmeters is 1.

  Hyperparameter 'theta'
    hyperid =

      `⁠80001⁠`

    name =

      `⁠log alpha⁠`

    short.name =

      `⁠alpha⁠`

    output.name =

      `⁠alpha for loglogistic observations⁠`

    output.name.intern =

      `⁠log alpha for loglogistic observations⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠25 25⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

Model 'loglogisticsurv'.
  Properties:
    doc =

      `⁠The loglogistic likelihood (survival)⁠`

    survival =

      `⁠TRUE⁠`

    discrete =

      `⁠FALSE⁠`

    link =

      `⁠default log neglog⁠`

    pdf =

      `⁠loglogistic⁠`

  Number of hyperparmeters is 11.

  Hyperparameter 'theta1'
    hyperid =

      `⁠80011⁠`

    name =

      `⁠log alpha⁠`

    short.name =

      `⁠alpha⁠`

    output.name =

      `⁠alpha for loglogisticsurv observations⁠`

    output.name.intern =

      `⁠log alpha for loglogisticsurv observations⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠25 25⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠80012⁠`

    name =

      `⁠beta1⁠`

    short.name =

      `⁠beta1⁠`

    output.name =

      `⁠beta1 for logLogistic-Cure⁠`

    output.name.intern =

      `⁠beta1 for logLogistic-Cure⁠`

    initial =

      `⁠-5⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠-4 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta3'
    hyperid =

      `⁠80013⁠`

    name =

      `⁠beta2⁠`

    short.name =

      `⁠beta2⁠`

    output.name =

      `⁠beta2 for logLogistic-Cure⁠`

    output.name.intern =

      `⁠beta2 for logLogistic-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta4'
    hyperid =

      `⁠80014⁠`

    name =

      `⁠beta3⁠`

    short.name =

      `⁠beta3⁠`

    output.name =

      `⁠beta3 for logLogistic-Cure⁠`

    output.name.intern =

      `⁠beta3 for logLogistic-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta5'
    hyperid =

      `⁠80015⁠`

    name =

      `⁠beta4⁠`

    short.name =

      `⁠beta4⁠`

    output.name =

      `⁠beta4 for logLogistic-Cure⁠`

    output.name.intern =

      `⁠beta4 for logLogistic-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta6'
    hyperid =

      `⁠80016⁠`

    name =

      `⁠beta5⁠`

    short.name =

      `⁠beta5⁠`

    output.name =

      `⁠beta5 for logLogistic-Cure⁠`

    output.name.intern =

      `⁠beta5 for logLogistic-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta7'
    hyperid =

      `⁠80017⁠`

    name =

      `⁠beta6⁠`

    short.name =

      `⁠beta6⁠`

    output.name =

      `⁠beta6 for logLogistic-Cure⁠`

    output.name.intern =

      `⁠beta6 for logLogistic-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta8'
    hyperid =

      `⁠80018⁠`

    name =

      `⁠beta7⁠`

    short.name =

      `⁠beta7⁠`

    output.name =

      `⁠beta7 for logLogistic-Cure⁠`

    output.name.intern =

      `⁠beta7 for logLogistic-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta9'
    hyperid =

      `⁠80019⁠`

    name =

      `⁠beta8⁠`

    short.name =

      `⁠beta8⁠`

    output.name =

      `⁠beta8 for logLogistic-Cure⁠`

    output.name.intern =

      `⁠beta8 for logLogistic-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta10'
    hyperid =

      `⁠80020⁠`

    name =

      `⁠beta9⁠`

    short.name =

      `⁠beta9⁠`

    output.name =

      `⁠beta9 for logLogistic-Cure⁠`

    output.name.intern =

      `⁠beta9 for logLogistic-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta11'
    hyperid =

      `⁠80021⁠`

    name =

      `⁠beta10⁠`

    short.name =

      `⁠beta10⁠`

    output.name =

      `⁠beta10 for logLogistic-Cure⁠`

    output.name.intern =

      `⁠beta10 for logLogistic-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

Model 'stochvol'.
  Properties:
    doc =

      `⁠The Gaussian stochvol likelihood⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠FALSE⁠`

    link =

      `⁠default log⁠`

    pdf =

      `⁠stochvolgaussian⁠`

  Number of hyperparmeters is 1.

  Hyperparameter 'theta'
    hyperid =

      `⁠82001⁠`

    name =

      `⁠log precision⁠`

    short.name =

      `⁠prec⁠`

    output.name =

      `⁠Offset precision for stochvol⁠`

    output.name.intern =

      `⁠Log offset precision for stochvol⁠`

    initial =

      `⁠500⁠`

    fixed =

      `⁠TRUE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 0.005⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

Model 'stochvolln'.
  Properties:
    doc =

      `⁠The Log-Normal stochvol likelihood⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠FALSE⁠`

    link =

      `⁠default log⁠`

    pdf =

      `⁠stochvolln⁠`

  Number of hyperparmeters is 1.

  Hyperparameter 'theta'
    hyperid =

      `⁠82011⁠`

    name =

      `⁠offset⁠`

    short.name =

      `⁠c⁠`

    output.name =

      `⁠Mean offset for stochvolln⁠`

    output.name.intern =

      `⁠Mean offset for stochvolln⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

Model 'stochvolsn'.
  Properties:
    doc =

      `⁠The SkewNormal stochvol likelihood⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠FALSE⁠`

    link =

      `⁠default log⁠`

    pdf =

      `⁠stochvolsn⁠`

  Number of hyperparmeters is 2.

  Hyperparameter 'theta1'
    hyperid =

      `⁠82101⁠`

    name =

      `⁠logit skew⁠`

    short.name =

      `⁠skew⁠`

    output.name =

      `⁠Skewness for stochvol_sn observations⁠`

    output.name.intern =

      `⁠Intern skewness for stochvol_sn observations⁠`

    initial =

      `⁠0.00123456789⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠pc.sn⁠`

    param =

      `⁠10⁠`

    to.theta =

      `⁠function(x, skew.max = 0.988) log((1 + x / skew.max) / (1 - x / skew.max))⁠`

    from.theta =

      `⁠function(x, skew.max = 0.988) skew.max * (2 * exp(x) / (1 + exp(x)) - 1)⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠82102⁠`

    name =

      `⁠log precision⁠`

    short.name =

      `⁠prec⁠`

    output.name =

      `⁠Offset precision for stochvol_sn⁠`

    output.name.intern =

      `⁠Log offset precision for stochvol_sn⁠`

    initial =

      `⁠500⁠`

    fixed =

      `⁠TRUE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 0.005⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

Model 'stochvolt'.
  Properties:
    doc =

      `⁠The Student-t stochvol likelihood⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠FALSE⁠`

    link =

      `⁠default log⁠`

    pdf =

      `⁠stochvolt⁠`

  Number of hyperparmeters is 1.

  Hyperparameter 'theta'
    hyperid =

      `⁠83001⁠`

    name =

      `⁠log degrees of freedom⁠`

    short.name =

      `⁠dof⁠`

    output.name =

      `⁠degrees of freedom for stochvol student-t⁠`

    output.name.intern =

      `⁠dof_intern for stochvol student-t⁠`

    initial =

      `⁠4⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠pc.dof⁠`

    param =

      `⁠15 0.5⁠`

    to.theta =

      `⁠function(x) log(x - 2)⁠`

    from.theta =

      `⁠function(x) 2 + exp(x)⁠`

Model 'stochvolnig'.
  Properties:
    doc =

      `⁠The Normal inverse Gaussian stochvol likelihood⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠FALSE⁠`

    link =

      `⁠default log⁠`

    pdf =

      `⁠stochvolnig⁠`

  Number of hyperparmeters is 2.

  Hyperparameter 'theta1'
    hyperid =

      `⁠84001⁠`

    name =

      `⁠skewness⁠`

    short.name =

      `⁠skew⁠`

    output.name.intern =

      `⁠skewness_param_intern for stochvol-nig⁠`

    output.name =

      `⁠skewness parameter for stochvol-nig⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠gaussian⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠84002⁠`

    name =

      `⁠shape⁠`

    short.name =

      `⁠shape⁠`

    output.name =

      `⁠shape parameter for stochvol-nig⁠`

    output.name.intern =

      `⁠shape_param_intern for stochvol-nig⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 0.5⁠`

    to.theta =

      `⁠function(x) log(x - 1)⁠`

    from.theta =

      `⁠function(x) 1 + exp(x)⁠`

Model 'zeroinflatedpoisson0'.
  Properties:
    doc =

      `⁠Zero-inflated Poisson, type 0⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠FALSE⁠`

    link =

      `⁠default log⁠`

    pdf =

      `⁠zeroinflated⁠`

  Number of hyperparmeters is 1.

  Hyperparameter 'theta'
    hyperid =

      `⁠85001⁠`

    name =

      `⁠logit probability⁠`

    short.name =

      `⁠prob⁠`

    output.name =

      `⁠zero-probability parameter for zero-inflated poisson_0⁠`

    output.name.intern =

      `⁠intern zero-probability parameter for zero-inflated poisson_0⁠`

    initial =

      `⁠-1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠gaussian⁠`

    param =

      `⁠-1 0.2⁠`

    to.theta =

      `⁠function(x) log(x / (1 - x))⁠`

    from.theta =

      `⁠function(x) exp(x) / (1 + exp(x))⁠`

Model 'zeroinflatedpoisson1'.
  Properties:
    doc =

      `⁠Zero-inflated Poisson, type 1⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠FALSE⁠`

    link =

      `⁠default log⁠`

    pdf =

      `⁠zeroinflated⁠`

  Number of hyperparmeters is 1.

  Hyperparameter 'theta'
    hyperid =

      `⁠86001⁠`

    name =

      `⁠logit probability⁠`

    short.name =

      `⁠prob⁠`

    output.name =

      `⁠zero-probability parameter for zero-inflated poisson_1⁠`

    output.name.intern =

      `⁠intern zero-probability parameter for zero-inflated poisson_1⁠`

    initial =

      `⁠-1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠gaussian⁠`

    param =

      `⁠-1 0.2⁠`

    to.theta =

      `⁠function(x) log(x / (1 - x))⁠`

    from.theta =

      `⁠function(x) exp(x) / (1 + exp(x))⁠`

Model 'zeroinflatedpoisson2'.
  Properties:
    doc =

      `⁠Zero-inflated Poisson, type 2⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠FALSE⁠`

    link =

      `⁠default log⁠`

    pdf =

      `⁠zeroinflated⁠`

  Number of hyperparmeters is 1.

  Hyperparameter 'theta'
    hyperid =

      `⁠87001⁠`

    name =

      `⁠log alpha⁠`

    short.name =

      `⁠a⁠`

    output.name =

      `⁠zero-probability parameter for zero-inflated poisson_2⁠`

    output.name.intern =

      `⁠intern zero-probability parameter for zero-inflated poisson_2⁠`

    initial =

      `⁠0.693147180559945⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠gaussian⁠`

    param =

      `⁠0.693147180559945 1⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

Model 'zeroinflatedcenpoisson0'.
  Properties:
    doc =

      `⁠Zero-inflated censored Poisson, type 0⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠FALSE⁠`

    link =

      `⁠default log⁠`

    pdf =

      `⁠zeroinflated⁠`

  Number of hyperparmeters is 1.

  Hyperparameter 'theta'
    hyperid =

      `⁠87101⁠`

    name =

      `⁠logit probability⁠`

    short.name =

      `⁠prob⁠`

    output.name =

      `⁠zero-probability parameter for zero-inflated poisson_0⁠`

    output.name.intern =

      `⁠intern zero-probability parameter for zero-inflated poisson_0⁠`

    initial =

      `⁠-1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠gaussian⁠`

    param =

      `⁠-1 0.2⁠`

    to.theta =

      `⁠function(x) log(x / (1 - x))⁠`

    from.theta =

      `⁠function(x) exp(x) / (1 + exp(x))⁠`

Model 'zeroinflatedcenpoisson1'.
  Properties:
    doc =

      `⁠Zero-inflated censored Poisson, type 1⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠FALSE⁠`

    link =

      `⁠default log⁠`

    pdf =

      `⁠zeroinflated⁠`

  Number of hyperparmeters is 1.

  Hyperparameter 'theta'
    hyperid =

      `⁠87201⁠`

    name =

      `⁠logit probability⁠`

    short.name =

      `⁠prob⁠`

    output.name =

      `⁠zero-probability parameter for zero-inflated poisson_1⁠`

    output.name.intern =

      `⁠intern zero-probability parameter for zero-inflated poisson_1⁠`

    initial =

      `⁠-1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠gaussian⁠`

    param =

      `⁠-1 0.2⁠`

    to.theta =

      `⁠function(x) log(x / (1 - x))⁠`

    from.theta =

      `⁠function(x) exp(x) / (1 + exp(x))⁠`

Model 'zeroinflatedbetabinomial0'.
  Properties:
    doc =

      `⁠Zero-inflated Beta-Binomial, type 0⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠TRUE⁠`

    link =

      `⁠default logit loga cauchit probit cloglog ccloglog loglog robit sn⁠`

    pdf =

      `⁠zeroinflated⁠`

  Number of hyperparmeters is 2.

  Hyperparameter 'theta1'
    hyperid =

      `⁠88001⁠`

    name =

      `⁠overdispersion⁠`

    short.name =

      `⁠rho⁠`

    output.name =

      `⁠rho for zero-inflated betabinomial_0⁠`

    output.name.intern =

      `⁠rho_intern for zero-inflated betabinomial_0⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠gaussian⁠`

    param =

      `⁠0 0.4⁠`

    to.theta =

      `⁠function(x) log(x / (1 - x))⁠`

    from.theta =

      `⁠function(x) exp(x) / (1 + exp(x))⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠88002⁠`

    name =

      `⁠logit probability⁠`

    short.name =

      `⁠prob⁠`

    output.name =

      `⁠zero-probability parameter for zero-inflated betabinomial_0⁠`

    output.name.intern =

      `⁠intern zero-probability parameter for zero-inflated betabinomial_0⁠`

    initial =

      `⁠-1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠gaussian⁠`

    param =

      `⁠-1 0.2⁠`

    to.theta =

      `⁠function(x) log(x / (1 - x))⁠`

    from.theta =

      `⁠function(x) exp(x) / (1 + exp(x))⁠`

Model 'zeroinflatedbetabinomial1'.
  Properties:
    doc =

      `⁠Zero-inflated Beta-Binomial, type 1⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠TRUE⁠`

    link =

      `⁠default logit loga cauchit probit cloglog ccloglog loglog robit sn⁠`

    pdf =

      `⁠zeroinflated⁠`

  Number of hyperparmeters is 2.

  Hyperparameter 'theta1'
    hyperid =

      `⁠89001⁠`

    name =

      `⁠overdispersion⁠`

    short.name =

      `⁠rho⁠`

    output.name =

      `⁠rho for zero-inflated betabinomial_1⁠`

    output.name.intern =

      `⁠rho_intern for zero-inflated betabinomial_1⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠gaussian⁠`

    param =

      `⁠0 0.4⁠`

    to.theta =

      `⁠function(x) log(x / (1 - x))⁠`

    from.theta =

      `⁠function(x) exp(x) / (1 + exp(x))⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠89002⁠`

    name =

      `⁠logit probability⁠`

    short.name =

      `⁠prob⁠`

    output.name =

      `⁠zero-probability parameter for zero-inflated betabinomial_1⁠`

    output.name.intern =

      `⁠intern zero-probability parameter for zero-inflated betabinomial_1⁠`

    initial =

      `⁠-1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠gaussian⁠`

    param =

      `⁠-1 0.2⁠`

    to.theta =

      `⁠function(x) log(x / (1 - x))⁠`

    from.theta =

      `⁠function(x) exp(x) / (1 + exp(x))⁠`

Model 'zeroinflatedbinomial0'.
  Properties:
    doc =

      `⁠Zero-inflated Binomial, type 0⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠FALSE⁠`

    link =

      `⁠default logit loga cauchit probit cloglog ccloglog loglog robit sn⁠`

    pdf =

      `⁠zeroinflated⁠`

  Number of hyperparmeters is 1.

  Hyperparameter 'theta'
    hyperid =

      `⁠90001⁠`

    name =

      `⁠logit probability⁠`

    short.name =

      `⁠prob⁠`

    output.name =

      `⁠zero-probability parameter for zero-inflated binomial_0⁠`

    output.name.intern =

      `⁠intern zero-probability parameter for zero-inflated binomial_0⁠`

    initial =

      `⁠-1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠gaussian⁠`

    param =

      `⁠-1 0.2⁠`

    to.theta =

      `⁠function(x) log(x / (1 - x))⁠`

    from.theta =

      `⁠function(x) exp(x) / (1 + exp(x))⁠`

Model 'zeroinflatedbinomial1'.
  Properties:
    doc =

      `⁠Zero-inflated Binomial, type 1⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠FALSE⁠`

    link =

      `⁠default logit loga cauchit probit cloglog ccloglog loglog robit sn⁠`

    pdf =

      `⁠zeroinflated⁠`

  Number of hyperparmeters is 1.

  Hyperparameter 'theta'
    hyperid =

      `⁠91001⁠`

    name =

      `⁠logit probability⁠`

    short.name =

      `⁠prob⁠`

    output.name =

      `⁠zero-probability parameter for zero-inflated binomial_1⁠`

    output.name.intern =

      `⁠intern zero-probability parameter for zero-inflated binomial_1⁠`

    initial =

      `⁠-1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠gaussian⁠`

    param =

      `⁠-1 0.2⁠`

    to.theta =

      `⁠function(x) log(x / (1 - x))⁠`

    from.theta =

      `⁠function(x) exp(x) / (1 + exp(x))⁠`

Model 'zeroinflatedbinomial2'.
  Properties:
    doc =

      `⁠Zero-inflated Binomial, type 2⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠FALSE⁠`

    link =

      `⁠default logit loga cauchit probit cloglog ccloglog loglog robit sn⁠`

    pdf =

      `⁠zeroinflated⁠`

  Number of hyperparmeters is 1.

  Hyperparameter 'theta'
    hyperid =

      `⁠92001⁠`

    name =

      `⁠alpha⁠`

    short.name =

      `⁠alpha⁠`

    output.name =

      `⁠zero-probability parameter for zero-inflated binomial_2⁠`

    output.name.intern =

      `⁠intern zero-probability parameter for zero-inflated binomial_2⁠`

    initial =

      `⁠-1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠gaussian⁠`

    param =

      `⁠-1 0.2⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

Model 'zeroninflatedbinomial2'.
  Properties:
    doc =

      `⁠Zero and N inflated binomial, type 2⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠FALSE⁠`

    link =

      `⁠default logit loga cauchit probit cloglog ccloglog loglog robit sn⁠`

    pdf =

      `⁠NA⁠`

  Number of hyperparmeters is 2.

  Hyperparameter 'theta1'
    hyperid =

      `⁠93001⁠`

    name =

      `⁠alpha1⁠`

    short.name =

      `⁠alpha1⁠`

    output.name =

      `⁠alpha1 parameter for zero-n-inflated binomial_2⁠`

    output.name.intern =

      `⁠intern alpha1 parameter for zero-n-inflated binomial_2⁠`

    initial =

      `⁠-1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠gaussian⁠`

    param =

      `⁠-1 0.2⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠93002⁠`

    name =

      `⁠alpha2⁠`

    short.name =

      `⁠alpha2⁠`

    output.name =

      `⁠alpha2 parameter for zero-n-inflated binomial_2⁠`

    output.name.intern =

      `⁠intern alpha2 parameter for zero-n-inflated binomial_2⁠`

    initial =

      `⁠-1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠gaussian⁠`

    param =

      `⁠-1 0.2⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

Model 'zeroninflatedbinomial3'.
  Properties:
    doc =

      `⁠Zero and N inflated binomial, type 3⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠FALSE⁠`

    link =

      `⁠default logit loga cauchit probit cloglog ccloglog loglog robit sn⁠`

    pdf =

      `⁠zeroinflated⁠`

  Number of hyperparmeters is 2.

  Hyperparameter 'theta1'
    hyperid =

      `⁠93101⁠`

    name =

      `⁠alpha0⁠`

    short.name =

      `⁠alpha0⁠`

    output.name =

      `⁠alpha0 parameter for zero-n-inflated binomial_3⁠`

    output.name.intern =

      `⁠intern alpha0 parameter for zero-n-inflated binomial_3⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 1⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠93102⁠`

    name =

      `⁠alphaN⁠`

    short.name =

      `⁠alphaN⁠`

    output.name.intern =

      `⁠intern alphaN parameter for zero-n-inflated binomial_3⁠`

    output.name =

      `⁠alphaN parameter for zero-n-inflated binomial_3⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 1⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

Model 'zeroinflatedbetabinomial2'.
  Properties:
    doc =

      `⁠Zero inflated Beta-Binomial, type 2⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠FALSE⁠`

    link =

      `⁠default logit loga cauchit probit cloglog ccloglog loglog robit sn⁠`

    pdf =

      `⁠zeroinflated⁠`

  Number of hyperparmeters is 2.

  Hyperparameter 'theta1'
    hyperid =

      `⁠94001⁠`

    name =

      `⁠log alpha⁠`

    short.name =

      `⁠a⁠`

    output.name =

      `⁠zero-probability parameter for zero-inflated betabinomial_2⁠`

    output.name.intern =

      `⁠intern zero-probability parameter for zero-inflated betabinomial_2⁠`

    initial =

      `⁠0.693147180559945⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠gaussian⁠`

    param =

      `⁠0.693147180559945 1⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠94002⁠`

    name =

      `⁠beta⁠`

    short.name =

      `⁠b⁠`

    output.name =

      `⁠overdispersion parameter for zero-inflated betabinomial_2⁠`

    output.name.intern =

      `⁠intern overdispersion parameter for zero-inflated betabinomial_2⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠gaussian⁠`

    param =

      `⁠0 1⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

Model 'zeroinflatednbinomial0'.
  Properties:
    doc =

      `⁠Zero inflated negBinomial, type 0⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠FALSE⁠`

    link =

      `⁠default log⁠`

    pdf =

      `⁠zeroinflated⁠`

  Number of hyperparmeters is 2.

  Hyperparameter 'theta1'
    hyperid =

      `⁠95001⁠`

    name =

      `⁠log size⁠`

    short.name =

      `⁠size⁠`

    output.name =

      `⁠size for nbinomial_0 zero-inflated observations⁠`

    output.name.intern =

      `⁠log size for nbinomial_0 zero-inflated observations⁠`

    initial =

      `⁠2.30258509299405⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠pc.mgamma⁠`

    param =

      `⁠7⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠95002⁠`

    name =

      `⁠logit probability⁠`

    short.name =

      `⁠prob⁠`

    output.name =

      `⁠zero-probability parameter for zero-inflated nbinomial_0⁠`

    output.name.intern =

      `⁠intern zero-probability parameter for zero-inflated nbinomial_0⁠`

    initial =

      `⁠-1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠gaussian⁠`

    param =

      `⁠-1 0.2⁠`

    to.theta =

      `⁠function(x) log(x / (1 - x))⁠`

    from.theta =

      `⁠function(x) exp(x) / (1 + exp(x))⁠`

Model 'zeroinflatednbinomial1'.
  Properties:
    doc =

      `⁠Zero inflated negBinomial, type 1⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠FALSE⁠`

    link =

      `⁠default log⁠`

    pdf =

      `⁠zeroinflated⁠`

  Number of hyperparmeters is 2.

  Hyperparameter 'theta1'
    hyperid =

      `⁠96001⁠`

    name =

      `⁠log size⁠`

    short.name =

      `⁠size⁠`

    output.name =

      `⁠size for nbinomial_1 zero-inflated observations⁠`

    output.name.intern =

      `⁠log size for nbinomial_1 zero-inflated observations⁠`

    initial =

      `⁠2.30258509299405⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠pc.mgamma⁠`

    param =

      `⁠7⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠96002⁠`

    name =

      `⁠logit probability⁠`

    short.name =

      `⁠prob⁠`

    output.name =

      `⁠zero-probability parameter for zero-inflated nbinomial_1⁠`

    output.name.intern =

      `⁠intern zero-probability parameter for zero-inflated nbinomial_1⁠`

    initial =

      `⁠-1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠gaussian⁠`

    param =

      `⁠-1 0.2⁠`

    to.theta =

      `⁠function(x) log(x / (1 - x))⁠`

    from.theta =

      `⁠function(x) exp(x) / (1 + exp(x))⁠`

Model 'zeroinflatednbinomial1strata2'.
  Properties:
    doc =

      `⁠Zero inflated negBinomial, type 1, strata 2⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠FALSE⁠`

    link =

      `⁠default log⁠`

    pdf =

      `⁠zeroinflated⁠`

  Number of hyperparmeters is 11.

  Hyperparameter 'theta1'
    hyperid =

      `⁠97001⁠`

    name =

      `⁠log size⁠`

    short.name =

      `⁠size⁠`

    output.name =

      `⁠size for zero-inflated nbinomial_1_strata2⁠`

    output.name.intern =

      `⁠log size for zero-inflated nbinomial_1_strata2⁠`

    initial =

      `⁠2.30258509299405⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠pc.mgamma⁠`

    param =

      `⁠7⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠97002⁠`

    name =

      `⁠logit probability 1⁠`

    short.name =

      `⁠prob1⁠`

    output.name =

      `⁠zero-probability1 for zero-inflated nbinomial_1_strata2⁠`

    output.name.intern =

      `⁠intern zero-probability1 for zero-inflated nbinomial_1_strata2⁠`

    initial =

      `⁠-1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠gaussian⁠`

    param =

      `⁠-1 0.2⁠`

    to.theta =

      `⁠function(x) log(x / (1 - x))⁠`

    from.theta =

      `⁠function(x) exp(x) / (1 + exp(x))⁠`

  Hyperparameter 'theta3'
    hyperid =

      `⁠97003⁠`

    name =

      `⁠logit probability 2⁠`

    short.name =

      `⁠prob2⁠`

    output.name =

      `⁠zero-probability2 for zero-inflated nbinomial_1_strata2⁠`

    output.name.intern =

      `⁠intern zero-probability2 for zero-inflated nbinomial_1_strata2⁠`

    initial =

      `⁠-1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠gaussian⁠`

    param =

      `⁠-1 0.2⁠`

    to.theta =

      `⁠function(x) log(x / (1 - x))⁠`

    from.theta =

      `⁠function(x) exp(x) / (1 + exp(x))⁠`

  Hyperparameter 'theta4'
    hyperid =

      `⁠97004⁠`

    name =

      `⁠logit probability 3⁠`

    short.name =

      `⁠prob3⁠`

    output.name =

      `⁠zero-probability3 for zero-inflated nbinomial_1_strata2⁠`

    output.name.intern =

      `⁠intern zero-probability3 for zero-inflated nbinomial_1_strata2⁠`

    initial =

      `⁠-1⁠`

    fixed =

      `⁠TRUE⁠`

    prior =

      `⁠gaussian⁠`

    param =

      `⁠-1 0.2⁠`

    to.theta =

      `⁠function(x) log(x / (1 - x))⁠`

    from.theta =

      `⁠function(x) exp(x) / (1 + exp(x))⁠`

  Hyperparameter 'theta5'
    hyperid =

      `⁠97005⁠`

    name =

      `⁠logit probability 4⁠`

    short.name =

      `⁠prob4⁠`

    output.name =

      `⁠zero-probability4 for zero-inflated nbinomial_1_strata2⁠`

    output.name.intern =

      `⁠intern zero-probability4 for zero-inflated nbinomial_1_strata2⁠`

    initial =

      `⁠-1⁠`

    fixed =

      `⁠TRUE⁠`

    prior =

      `⁠gaussian⁠`

    param =

      `⁠-1 0.2⁠`

    to.theta =

      `⁠function(x) log(x / (1 - x))⁠`

    from.theta =

      `⁠function(x) exp(x) / (1 + exp(x))⁠`

  Hyperparameter 'theta6'
    hyperid =

      `⁠97006⁠`

    name =

      `⁠logit probability 5⁠`

    short.name =

      `⁠prob5⁠`

    output.name =

      `⁠zero-probability5 for zero-inflated nbinomial_1_strata2⁠`

    output.name.intern =

      `⁠intern zero-probability5 for zero-inflated nbinomial_1_strata2⁠`

    initial =

      `⁠-1⁠`

    fixed =

      `⁠TRUE⁠`

    prior =

      `⁠gaussian⁠`

    param =

      `⁠-1 0.2⁠`

    to.theta =

      `⁠function(x) log(x / (1 - x))⁠`

    from.theta =

      `⁠function(x) exp(x) / (1 + exp(x))⁠`

  Hyperparameter 'theta7'
    hyperid =

      `⁠97007⁠`

    name =

      `⁠logit probability 6⁠`

    short.name =

      `⁠prob6⁠`

    output.name =

      `⁠zero-probability6 for zero-inflated nbinomial_1_strata2⁠`

    output.name.intern =

      `⁠intern zero-probability6 for zero-inflated nbinomial_1_strata2⁠`

    initial =

      `⁠-1⁠`

    fixed =

      `⁠TRUE⁠`

    prior =

      `⁠gaussian⁠`

    param =

      `⁠-1 0.2⁠`

    to.theta =

      `⁠function(x) log(x / (1 - x))⁠`

    from.theta =

      `⁠function(x) exp(x) / (1 + exp(x))⁠`

  Hyperparameter 'theta8'
    hyperid =

      `⁠97008⁠`

    name =

      `⁠logit probability 7⁠`

    short.name =

      `⁠prob7⁠`

    output.name =

      `⁠zero-probability7 for zero-inflated nbinomial_1_strata2⁠`

    output.name.intern =

      `⁠intern zero-probability7 for zero-inflated nbinomial_1_strata2⁠`

    initial =

      `⁠-1⁠`

    fixed =

      `⁠TRUE⁠`

    prior =

      `⁠gaussian⁠`

    param =

      `⁠-1 0.2⁠`

    to.theta =

      `⁠function(x) log(x / (1 - x))⁠`

    from.theta =

      `⁠function(x) exp(x) / (1 + exp(x))⁠`

  Hyperparameter 'theta9'
    hyperid =

      `⁠97009⁠`

    name =

      `⁠logit probability 8⁠`

    short.name =

      `⁠prob8⁠`

    output.name =

      `⁠zero-probability8 for zero-inflated nbinomial_1_strata2⁠`

    output.name.intern =

      `⁠intern zero-probability8 for zero-inflated nbinomial_1_strata2⁠`

    initial =

      `⁠-1⁠`

    fixed =

      `⁠TRUE⁠`

    prior =

      `⁠gaussian⁠`

    param =

      `⁠-1 0.2⁠`

    to.theta =

      `⁠function(x) log(x / (1 - x))⁠`

    from.theta =

      `⁠function(x) exp(x) / (1 + exp(x))⁠`

  Hyperparameter 'theta10'
    hyperid =

      `⁠97010⁠`

    name =

      `⁠logit probability 9⁠`

    short.name =

      `⁠prob9⁠`

    output.name =

      `⁠zero-probability9 for zero-inflated nbinomial_1_strata2⁠`

    output.name.intern =

      `⁠intern zero-probability9 for zero-inflated nbinomial_1_strata2⁠`

    initial =

      `⁠-1⁠`

    fixed =

      `⁠TRUE⁠`

    prior =

      `⁠gaussian⁠`

    param =

      `⁠-1 0.2⁠`

    to.theta =

      `⁠function(x) log(x / (1 - x))⁠`

    from.theta =

      `⁠function(x) exp(x) / (1 + exp(x))⁠`

  Hyperparameter 'theta11'
    hyperid =

      `⁠97011⁠`

    name =

      `⁠logit probability 10⁠`

    short.name =

      `⁠prob10⁠`

    output.name =

      `⁠zero-probability10 for zero-inflated nbinomial_1_strata2⁠`

    output.name.intern =

      `⁠intern zero-probability10 for zero-inflated nbinomial_1_strata2⁠`

    initial =

      `⁠-1⁠`

    fixed =

      `⁠TRUE⁠`

    prior =

      `⁠gaussian⁠`

    param =

      `⁠-1 0.2⁠`

    to.theta =

      `⁠function(x) log(x / (1 - x))⁠`

    from.theta =

      `⁠function(x) exp(x) / (1 + exp(x))⁠`

Model 'zeroinflatednbinomial1strata3'.
  Properties:
    doc =

      `⁠Zero inflated negBinomial, type 1, strata 3⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠FALSE⁠`

    link =

      `⁠default log⁠`

    pdf =

      `⁠zeroinflated⁠`

  Number of hyperparmeters is 11.

  Hyperparameter 'theta1'
    hyperid =

      `⁠98001⁠`

    name =

      `⁠logit probability⁠`

    short.name =

      `⁠prob⁠`

    output.name =

      `⁠zero-probability for zero-inflated nbinomial_1_strata3⁠`

    output.name.intern =

      `⁠intern zero-probability for zero-inflated nbinomial_1_strata3⁠`

    initial =

      `⁠-1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠gaussian⁠`

    param =

      `⁠-1 0.2⁠`

    to.theta =

      `⁠function(x) log(x / (1 - x))⁠`

    from.theta =

      `⁠function(x) exp(x) / (1 + exp(x))⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠98002⁠`

    name =

      `⁠log size 1⁠`

    short.name =

      `⁠size1⁠`

    output.name =

      `⁠size1 for zero-inflated nbinomial_1_strata3⁠`

    output.name.intern =

      `⁠log_size1 for zero-inflated nbinomial_1_strata3⁠`

    initial =

      `⁠2.30258509299405⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠pc.mgamma⁠`

    param =

      `⁠7⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta3'
    hyperid =

      `⁠98003⁠`

    name =

      `⁠log size 2⁠`

    short.name =

      `⁠size2⁠`

    output.name =

      `⁠size2 for zero-inflated nbinomial_1_strata3⁠`

    output.name.intern =

      `⁠log_size2 for zero-inflated nbinomial_1_strata3⁠`

    initial =

      `⁠2.30258509299405⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠pc.mgamma⁠`

    param =

      `⁠7⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta4'
    hyperid =

      `⁠98004⁠`

    name =

      `⁠log size 3⁠`

    short.name =

      `⁠size3⁠`

    output.name =

      `⁠size3 for zero-inflated nbinomial_1_strata3⁠`

    output.name.intern =

      `⁠log_size3 for zero-inflated nbinomial_1_strata3⁠`

    initial =

      `⁠2.30258509299405⁠`

    fixed =

      `⁠TRUE⁠`

    prior =

      `⁠pc.mgamma⁠`

    param =

      `⁠7⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta5'
    hyperid =

      `⁠98005⁠`

    name =

      `⁠log size 4⁠`

    short.name =

      `⁠size4⁠`

    output.name =

      `⁠size4 for zero-inflated nbinomial_1_strata3⁠`

    output.name.intern =

      `⁠log_size4 for zero-inflated nbinomial_1_strata3⁠`

    initial =

      `⁠2.30258509299405⁠`

    fixed =

      `⁠TRUE⁠`

    prior =

      `⁠pc.mgamma⁠`

    param =

      `⁠7⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta6'
    hyperid =

      `⁠98006⁠`

    name =

      `⁠log size 5⁠`

    short.name =

      `⁠size5⁠`

    output.name =

      `⁠size5 for zero-inflated nbinomial_1_strata3⁠`

    output.name.intern =

      `⁠log_size5 for zero-inflated nbinomial_1_strata3⁠`

    initial =

      `⁠2.30258509299405⁠`

    fixed =

      `⁠TRUE⁠`

    prior =

      `⁠pc.mgamma⁠`

    param =

      `⁠7⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta7'
    hyperid =

      `⁠98007⁠`

    name =

      `⁠log size 6⁠`

    short.name =

      `⁠size6⁠`

    output.name =

      `⁠size6 for zero-inflated nbinomial_1_strata3⁠`

    output.name.intern =

      `⁠log_size6 for zero-inflated nbinomial_1_strata3⁠`

    initial =

      `⁠2.30258509299405⁠`

    fixed =

      `⁠TRUE⁠`

    prior =

      `⁠pc.mgamma⁠`

    param =

      `⁠7⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta8'
    hyperid =

      `⁠98008⁠`

    name =

      `⁠log size 7⁠`

    short.name =

      `⁠size7⁠`

    output.name =

      `⁠size7 for zero-inflated nbinomial_1_strata3⁠`

    output.name.intern =

      `⁠log_size7 for zero-inflated nbinomial_1_strata3⁠`

    initial =

      `⁠2.30258509299405⁠`

    fixed =

      `⁠TRUE⁠`

    prior =

      `⁠pc.mgamma⁠`

    param =

      `⁠7⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta9'
    hyperid =

      `⁠98009⁠`

    name =

      `⁠log size 8⁠`

    short.name =

      `⁠size8⁠`

    output.name =

      `⁠size8 for zero-inflated nbinomial_1_strata3⁠`

    output.name.intern =

      `⁠log_size8 for zero-inflated nbinomial_1_strata3⁠`

    initial =

      `⁠2.30258509299405⁠`

    fixed =

      `⁠TRUE⁠`

    prior =

      `⁠pc.mgamma⁠`

    param =

      `⁠7⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta10'
    hyperid =

      `⁠98010⁠`

    name =

      `⁠log size 9⁠`

    short.name =

      `⁠size9⁠`

    output.name =

      `⁠size9 for zero-inflated nbinomial_1_strata3⁠`

    output.name.intern =

      `⁠log_size9 for zero-inflated nbinomial_1_strata3⁠`

    initial =

      `⁠2.30258509299405⁠`

    fixed =

      `⁠TRUE⁠`

    prior =

      `⁠pc.mgamma⁠`

    param =

      `⁠7⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta11'
    hyperid =

      `⁠98011⁠`

    name =

      `⁠log size 10⁠`

    short.name =

      `⁠size10⁠`

    output.name =

      `⁠size10 for zero-inflated nbinomial_1_strata3⁠`

    output.name.intern =

      `⁠log_size10 for zero-inflated nbinomial_1_strata3⁠`

    initial =

      `⁠2.30258509299405⁠`

    fixed =

      `⁠TRUE⁠`

    prior =

      `⁠pc.mgamma⁠`

    param =

      `⁠7⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

Model 'zeroinflatednbinomial2'.
  Properties:
    doc =

      `⁠Zero inflated negBinomial, type 2⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠FALSE⁠`

    link =

      `⁠default log⁠`

    pdf =

      `⁠zeroinflated⁠`

  Number of hyperparmeters is 2.

  Hyperparameter 'theta1'
    hyperid =

      `⁠99001⁠`

    name =

      `⁠log size⁠`

    short.name =

      `⁠size⁠`

    output.name =

      `⁠size for nbinomial zero-inflated observations⁠`

    output.name.inter =

      `⁠log size for nbinomial zero-inflated observations⁠`

    initial =

      `⁠2.30258509299405⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠pc.mgamma⁠`

    param =

      `⁠7⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠99002⁠`

    name =

      `⁠log alpha⁠`

    short.name =

      `⁠a⁠`

    output.name =

      `⁠parameter alpha for zero-inflated nbinomial2⁠`

    output.name.intern =

      `⁠parameter alpha.intern for zero-inflated nbinomial2⁠`

    initial =

      `⁠0.693147180559945⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠gaussian⁠`

    param =

      `⁠2 1⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

Model 't'.
  Properties:
    doc =

      `⁠Student-t likelihood⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠FALSE⁠`

    link =

      `⁠default identity⁠`

    pdf =

      `⁠student-t⁠`

  Number of hyperparmeters is 2.

  Hyperparameter 'theta1'
    hyperid =

      `⁠100001⁠`

    name =

      `⁠log precision⁠`

    short.name =

      `⁠prec⁠`

    output.name =

      `⁠precision for the student-t observations⁠`

    output.name.intern =

      `⁠log precision for the student-t observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 5e-05⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠100002⁠`

    name =

      `⁠log degrees of freedom⁠`

    short.name =

      `⁠dof⁠`

    output.name =

      `⁠degrees of freedom for student-t⁠`

    output.name.intern =

      `⁠dof_intern for student-t⁠`

    initial =

      `⁠5⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠pc.dof⁠`

    param =

      `⁠15 0.5⁠`

    to.theta =

      `⁠function(x) log(x - 2)⁠`

    from.theta =

      `⁠function(x) 2 + exp(x)⁠`

Model 'tstrata'.
  Properties:
    doc =

      `⁠A stratified version of the Student-t likelihood⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠FALSE⁠`

    link =

      `⁠default identity⁠`

    pdf =

      `⁠tstrata⁠`

  Number of hyperparmeters is 11.

  Hyperparameter 'theta1'
    hyperid =

      `⁠101001⁠`

    name =

      `⁠log degrees of freedom⁠`

    short.name =

      `⁠dof⁠`

    output.name.intern =

      `⁠dof_intern for tstrata⁠`

    output.name =

      `⁠degrees of freedom for tstrata⁠`

    initial =

      `⁠4⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠pc.dof⁠`

    param =

      `⁠15 0.5⁠`

    to.theta =

      `⁠function(x) log(x - 5)⁠`

    from.theta =

      `⁠function(x) 5 + exp(x)⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠101002⁠`

    name =

      `⁠log precision1⁠`

    short.name =

      `⁠prec1⁠`

    output.name =

      `⁠Prec for tstrata strata⁠`

    output.name.intern =

      `⁠Log prec for tstrata strata⁠`

    initial =

      `⁠2⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 5e-05⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta3'
    hyperid =

      `⁠101003⁠`

    name =

      `⁠log precision2⁠`

    short.name =

      `⁠prec2⁠`

    output.name =

      `⁠Prec for tstrata strata[2]⁠`

    output.name.intern =

      `⁠Log prec for tstrata strata[2]⁠`

    initial =

      `⁠2⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 5e-05⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta4'
    hyperid =

      `⁠101004⁠`

    name =

      `⁠log precision3⁠`

    short.name =

      `⁠prec3⁠`

    output.name =

      `⁠Prec for tstrata strata[3]⁠`

    output.name.intern =

      `⁠Log prec for tstrata strata[3]⁠`

    initial =

      `⁠2⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 5e-05⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta5'
    hyperid =

      `⁠101005⁠`

    name =

      `⁠log precision4⁠`

    short.name =

      `⁠prec4⁠`

    output.name =

      `⁠Prec for tstrata strata[4]⁠`

    output.name.intern =

      `⁠Log prec for tstrata strata[4]⁠`

    initial =

      `⁠2⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 5e-05⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta6'
    hyperid =

      `⁠101006⁠`

    name =

      `⁠log precision5⁠`

    short.name =

      `⁠prec5⁠`

    output.name =

      `⁠Prec for tstrata strata[5]⁠`

    output.name.intern =

      `⁠Log prec for tstrata strata[5]⁠`

    initial =

      `⁠2⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 5e-05⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta7'
    hyperid =

      `⁠101007⁠`

    name =

      `⁠log precision6⁠`

    short.name =

      `⁠prec6⁠`

    output.name =

      `⁠Prec for tstrata strata[6]⁠`

    output.name.intern =

      `⁠Log prec for tstrata strata[6]⁠`

    initial =

      `⁠2⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 5e-05⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta8'
    hyperid =

      `⁠101008⁠`

    name =

      `⁠log precision7⁠`

    short.name =

      `⁠prec7⁠`

    output.name =

      `⁠Prec for tstrata strata[7]⁠`

    output.name.intern =

      `⁠Log prec for tstrata strata[7]⁠`

    initial =

      `⁠2⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 5e-05⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta9'
    hyperid =

      `⁠101009⁠`

    name =

      `⁠log precision8⁠`

    short.name =

      `⁠prec8⁠`

    output.name =

      `⁠Prec for tstrata strata[8]⁠`

    output.name.intern =

      `⁠Log prec for tstrata strata[8]⁠`

    initial =

      `⁠2⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 5e-05⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta10'
    hyperid =

      `⁠101010⁠`

    name =

      `⁠log precision9⁠`

    short.name =

      `⁠prec9⁠`

    output.name =

      `⁠Prec for tstrata strata[9]⁠`

    output.name.intern =

      `⁠Log prec for tstrata strata[9]⁠`

    initial =

      `⁠2⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 5e-05⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta11'
    hyperid =

      `⁠101011⁠`

    name =

      `⁠log precision10⁠`

    short.name =

      `⁠prec10⁠`

    output.name =

      `⁠Prec for tstrata strata[10]⁠`

    output.name.intern =

      `⁠Log prec for tstrata strata[10]⁠`

    initial =

      `⁠2⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 5e-05⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

Model 'nmix'.
  Properties:
    doc =

      `⁠Binomial-Poisson mixture⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠TRUE⁠`

    link =

      `⁠default logit loga probit⁠`

    pdf =

      `⁠nmix⁠`

  Number of hyperparmeters is 15.

  Hyperparameter 'theta1'
    hyperid =

      `⁠101101⁠`

    name =

      `⁠beta1⁠`

    short.name =

      `⁠beta1⁠`

    output.name =

      `⁠beta[1] for NMix observations⁠`

    output.name.intern =

      `⁠beta[1] for NMix observations⁠`

    initial =

      `⁠2.30258509299405⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 0.5⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠101102⁠`

    name =

      `⁠beta2⁠`

    short.name =

      `⁠beta2⁠`

    output.name =

      `⁠beta[2] for NMix observations⁠`

    output.name.intern =

      `⁠beta[2] for NMix observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 1⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta3'
    hyperid =

      `⁠101103⁠`

    name =

      `⁠beta3⁠`

    short.name =

      `⁠beta3⁠`

    output.name =

      `⁠beta[3] for NMix observations⁠`

    output.name.intern =

      `⁠beta[3] for NMix observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 1⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta4'
    hyperid =

      `⁠101104⁠`

    name =

      `⁠beta4⁠`

    short.name =

      `⁠beta4⁠`

    output.name =

      `⁠beta[4] for NMix observations⁠`

    output.name.intern =

      `⁠beta[4] for NMix observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 1⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta5'
    hyperid =

      `⁠101105⁠`

    name =

      `⁠beta5⁠`

    short.name =

      `⁠beta5⁠`

    output.name =

      `⁠beta[5] for NMix observations⁠`

    output.name.intern =

      `⁠beta[5] for NMix observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 1⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta6'
    hyperid =

      `⁠101106⁠`

    name =

      `⁠beta6⁠`

    short.name =

      `⁠beta6⁠`

    output.name =

      `⁠beta[6] for NMix observations⁠`

    output.name.intern =

      `⁠beta[6] for NMix observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 1⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta7'
    hyperid =

      `⁠101107⁠`

    name =

      `⁠beta7⁠`

    short.name =

      `⁠beta7⁠`

    output.name =

      `⁠beta[7] for NMix observations⁠`

    output.name.intern =

      `⁠beta[7] for NMix observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 1⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta8'
    hyperid =

      `⁠101108⁠`

    name =

      `⁠beta8⁠`

    short.name =

      `⁠beta8⁠`

    output.name =

      `⁠beta[8] for NMix observations⁠`

    output.name.intern =

      `⁠beta[8] for NMix observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 1⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta9'
    hyperid =

      `⁠101109⁠`

    name =

      `⁠beta9⁠`

    short.name =

      `⁠beta9⁠`

    output.name =

      `⁠beta[9] for NMix observations⁠`

    output.name.intern =

      `⁠beta[9] for NMix observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 1⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta10'
    hyperid =

      `⁠101110⁠`

    name =

      `⁠beta10⁠`

    short.name =

      `⁠beta10⁠`

    output.name =

      `⁠beta[10] for NMix observations⁠`

    output.name.intern =

      `⁠beta[10] for NMix observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 1⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta11'
    hyperid =

      `⁠101111⁠`

    name =

      `⁠beta11⁠`

    short.name =

      `⁠beta11⁠`

    output.name =

      `⁠beta[11] for NMix observations⁠`

    output.name.intern =

      `⁠beta[11] for NMix observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 1⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta12'
    hyperid =

      `⁠101112⁠`

    name =

      `⁠beta12⁠`

    short.name =

      `⁠beta12⁠`

    output.name =

      `⁠beta[12] for NMix observations⁠`

    output.name.intern =

      `⁠beta[12] for NMix observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 1⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta13'
    hyperid =

      `⁠101113⁠`

    name =

      `⁠beta13⁠`

    short.name =

      `⁠beta13⁠`

    output.name =

      `⁠beta[13] for NMix observations⁠`

    output.name.intern =

      `⁠beta[13] for NMix observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 1⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta14'
    hyperid =

      `⁠101114⁠`

    name =

      `⁠beta14⁠`

    short.name =

      `⁠beta14⁠`

    output.name =

      `⁠beta[14] for NMix observations⁠`

    output.name.intern =

      `⁠beta[14] for NMix observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 1⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta15'
    hyperid =

      `⁠101115⁠`

    name =

      `⁠beta15⁠`

    short.name =

      `⁠beta15⁠`

    output.name =

      `⁠beta[15] for NMix observations⁠`

    output.name.intern =

      `⁠beta[15] for NMix observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 1⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

Model 'nmixnb'.
  Properties:
    doc =

      `⁠NegBinomial-Poisson mixture⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠TRUE⁠`

    link =

      `⁠default logit loga probit⁠`

    pdf =

      `⁠nmixnb⁠`

  Number of hyperparmeters is 16.

  Hyperparameter 'theta1'
    hyperid =

      `⁠101121⁠`

    name =

      `⁠beta1⁠`

    short.name =

      `⁠beta1⁠`

    output.name =

      `⁠beta[1] for NMixNB observations⁠`

    output.name.intern =

      `⁠beta[1] for NMixNB observations⁠`

    initial =

      `⁠2.30258509299405⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 0.5⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠101122⁠`

    name =

      `⁠beta2⁠`

    short.name =

      `⁠beta2⁠`

    output.name =

      `⁠beta[2] for NMixNB observations⁠`

    output.name.intern =

      `⁠beta[2] for NMixNB observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 1⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta3'
    hyperid =

      `⁠101123⁠`

    name =

      `⁠beta3⁠`

    short.name =

      `⁠beta3⁠`

    output.name =

      `⁠beta[3] for NMixNB observations⁠`

    output.name.intern =

      `⁠beta[3] for NMixNB observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 1⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta4'
    hyperid =

      `⁠101124⁠`

    name =

      `⁠beta4⁠`

    short.name =

      `⁠beta4⁠`

    output.name =

      `⁠beta[4] for NMixNB observations⁠`

    output.name.intern =

      `⁠beta[4] for NMixNB observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 1⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta5'
    hyperid =

      `⁠101125⁠`

    name =

      `⁠beta5⁠`

    short.name =

      `⁠beta5⁠`

    output.name =

      `⁠beta[5] for NMixNB observations⁠`

    output.name.intern =

      `⁠beta[5] for NMixNB observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 1⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta6'
    hyperid =

      `⁠101126⁠`

    name =

      `⁠beta6⁠`

    short.name =

      `⁠beta6⁠`

    output.name =

      `⁠beta[6] for NMixNB observations⁠`

    output.name.intern =

      `⁠beta[6] for NMixNB observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 1⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta7'
    hyperid =

      `⁠101127⁠`

    name =

      `⁠beta7⁠`

    short.name =

      `⁠beta7⁠`

    output.name =

      `⁠beta[7] for NMixNB observations⁠`

    output.name.intern =

      `⁠beta[7] for NMixNB observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 1⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta8'
    hyperid =

      `⁠101128⁠`

    name =

      `⁠beta8⁠`

    short.name =

      `⁠beta8⁠`

    output.name =

      `⁠beta[8] for NMixNB observations⁠`

    output.name.intern =

      `⁠beta[8] for NMixNB observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 1⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta9'
    hyperid =

      `⁠101129⁠`

    name =

      `⁠beta9⁠`

    short.name =

      `⁠beta9⁠`

    output.name =

      `⁠beta[9] for NMixNB observations⁠`

    output.name.intern =

      `⁠beta[9] for NMixNB observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 1⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta10'
    hyperid =

      `⁠101130⁠`

    name =

      `⁠beta10⁠`

    short.name =

      `⁠beta10⁠`

    output.name =

      `⁠beta[10] for NMixNB observations⁠`

    output.name.intern =

      `⁠beta[10] for NMixNB observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 1⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta11'
    hyperid =

      `⁠101131⁠`

    name =

      `⁠beta11⁠`

    short.name =

      `⁠beta11⁠`

    output.name =

      `⁠beta[11] for NMixNB observations⁠`

    output.name.intern =

      `⁠beta[11] for NMixNB observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 1⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta12'
    hyperid =

      `⁠101132⁠`

    name =

      `⁠beta12⁠`

    short.name =

      `⁠beta12⁠`

    output.name =

      `⁠beta[12] for NMixNB observations⁠`

    output.name.intern =

      `⁠beta[12] for NMixNB observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 1⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta13'
    hyperid =

      `⁠101133⁠`

    name =

      `⁠beta13⁠`

    short.name =

      `⁠beta13⁠`

    output.name =

      `⁠beta[13] for NMixNB observations⁠`

    output.name.intern =

      `⁠beta[13] for NMixNB observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 1⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta14'
    hyperid =

      `⁠101134⁠`

    name =

      `⁠beta14⁠`

    short.name =

      `⁠beta14⁠`

    output.name =

      `⁠beta[14] for NMixNB observations⁠`

    output.name.intern =

      `⁠beta[14] for NMixNB observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 1⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta15'
    hyperid =

      `⁠101135⁠`

    name =

      `⁠beta15⁠`

    short.name =

      `⁠beta15⁠`

    output.name =

      `⁠beta[15] for NMixNB observations⁠`

    output.name.intern =

      `⁠beta[15] for NMixNB observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 1⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta16'
    hyperid =

      `⁠101136⁠`

    name =

      `⁠overdispersion⁠`

    short.name =

      `⁠overdispersion⁠`

    output.name =

      `⁠overdispersion for NMixNB observations⁠`

    output.name.intern =

      `⁠log_overdispersion for NMixNB observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠pc.gamma⁠`

    param =

      `⁠7⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

Model 'gp'.
  Properties:
    doc =

      `⁠Generalized Pareto likelihood⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠TRUE⁠`

    link =

      `⁠default quantile⁠`

    pdf =

      `⁠genPareto⁠`

  Number of hyperparmeters is 1.

  Hyperparameter 'theta'
    hyperid =

      `⁠101201⁠`

    name =

      `⁠tail⁠`

    short.name =

      `⁠xi⁠`

    output.name =

      `⁠Tail parameter for the gp observations⁠`

    output.name.intern =

      `⁠Intern tail parameter for the gp observations⁠`

    initial =

      `⁠-4⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠pc.gevtail⁠`

    param =

      `⁠7 0 0.5⁠`

    to.theta =

      `⁠function(x, interval = c(REPLACE.ME.low, REPLACE.ME.high)) log(-(interval[1] - x) / (interval[2] - x))⁠`

    from.theta =

      `⁠function(x, interval = c(REPLACE.ME.low, REPLACE.ME.high)) interval[1] + (interval[2] - interval[1]) * exp(x) / (1.0 + exp(x))⁠`

Model 'egp'.
  Properties:
    doc =

      `⁠Exteneded Generalized Pareto likelihood⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠FALSE⁠`

    link =

      `⁠default quantile⁠`

    pdf =

      `⁠egp⁠`

  Number of hyperparmeters is 2.

  Hyperparameter 'theta1'
    hyperid =

      `⁠101211⁠`

    name =

      `⁠tail⁠`

    short.name =

      `⁠xi⁠`

    output.name =

      `⁠Tail parameter for egp observations⁠`

    output.name.intern =

      `⁠Intern tail parameter for egp observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠pc.egptail⁠`

    param =

      `⁠5 -0.5 0.5⁠`

    to.theta =

      `⁠function(x, interval = c(REPLACE.ME.low, REPLACE.ME.high)) log(-(interval[1] - x) / (interval[2] - x))⁠`

    from.theta =

      `⁠function(x, interval = c(REPLACE.ME.low, REPLACE.ME.high)) interval[1] + (interval[2] - interval[1]) * exp(x) / (1.0 + exp(x))⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠101212⁠`

    name =

      `⁠shape⁠`

    short.name =

      `⁠kappa⁠`

    output.name =

      `⁠Shape parameter for the egp observations⁠`

    output.name.intern =

      `⁠Intern shape parameter for the egp observations⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠100 100⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

Model 'dgp'.
  Properties:
    doc =

      `⁠Discrete generalized Pareto likelihood⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠TRUE⁠`

    link =

      `⁠default quantile⁠`

    pdf =

      `⁠dgp⁠`

  Number of hyperparmeters is 1.

  Hyperparameter 'theta'
    hyperid =

      `⁠101301⁠`

    name =

      `⁠tail⁠`

    short.name =

      `⁠xi⁠`

    output.name =

      `⁠Tail parameter for the dgp observations⁠`

    output.name.intern =

      `⁠Intern tail parameter for the dgp observations⁠`

    initial =

      `⁠2⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠pc.gevtail⁠`

    param =

      `⁠7 0 0.5⁠`

    to.theta =

      `⁠function(x, interval = c(REPLACE.ME.low, REPLACE.ME.high)) log(-(interval[1] - x) / (interval[2] - x))⁠`

    from.theta =

      `⁠function(x, interval = c(REPLACE.ME.low, REPLACE.ME.high)) interval[1] + (interval[2] - interval[1]) * exp(x) / (1.0 + exp(x))⁠`

Model 'logperiodogram'.
  Properties:
    doc =

      `⁠Likelihood for the log-periodogram⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠FALSE⁠`

    link =

      `⁠default identity⁠`

    pdf =

      `⁠NA⁠`

  Number of hyperparmeters is 0.

Model 'tweedie'.
  Properties:
    doc =

      `⁠Tweedie distribution⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠FALSE⁠`

    link =

      `⁠default log⁠`

    pdf =

      `⁠tweedie⁠`

  Number of hyperparmeters is 2.

  Hyperparameter 'theta1'
    hyperid =

      `⁠102101⁠`

    name =

      `⁠p⁠`

    short.name =

      `⁠p⁠`

    output.name =

      `⁠p parameter for Tweedie⁠`

    output.name.intern =

      `⁠p_intern parameter for Tweedie⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x, interval = c(1.0, 2.0)) log(-(interval[1] - x) / (interval[2] - x))⁠`

    from.theta =

      `⁠function(x, interval = c(1.0, 2.0)) interval[1] + (interval[2] - interval[1]) * exp(x) / (1.0 + exp(x))⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠102201⁠`

    name =

      `⁠dispersion⁠`

    short.name =

      `⁠phi⁠`

    output.name =

      `⁠Dispersion parameter for Tweedie⁠`

    output.name.intern =

      `⁠Log dispersion parameter for Tweedie⁠`

    initial =

      `⁠-4⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠100 100⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

Model 'fmri'.
  Properties:
    doc =

      `⁠fmri distribution (special nc-chi)⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠FALSE⁠`

    link =

      `⁠default log⁠`

    pdf =

      `⁠fmri⁠`

  Number of hyperparmeters is 2.

  Hyperparameter 'theta1'
    hyperid =

      `⁠103101⁠`

    name =

      `⁠precision⁠`

    short.name =

      `⁠prec⁠`

    output.name =

      `⁠Precision for fmri⁠`

    output.name.intern =

      `⁠Log precision for fmri⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠10 10⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠103202⁠`

    name =

      `⁠dof⁠`

    short.name =

      `⁠df⁠`

    output.name =

      `⁠NOT IN USE⁠`

    output.name.intern =

      `⁠NOT IN USE⁠`

    initial =

      `⁠4⁠`

    fixed =

      `⁠TRUE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 1⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

Model 'fmrisurv'.
  Properties:
    doc =

      `⁠fmri distribution (special nc-chi)⁠`

    survival =

      `⁠TRUE⁠`

    discrete =

      `⁠FALSE⁠`

    link =

      `⁠default log⁠`

    pdf =

      `⁠fmri⁠`

  Number of hyperparmeters is 2.

  Hyperparameter 'theta1'
    hyperid =

      `⁠104101⁠`

    name =

      `⁠precision⁠`

    short.name =

      `⁠prec⁠`

    output.name =

      `⁠Precision for fmrisurv⁠`

    output.name.intern =

      `⁠Log precision for fmrisurv⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠10 10⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠104201⁠`

    name =

      `⁠dof⁠`

    short.name =

      `⁠df⁠`

    output.name =

      `⁠NOT IN USE⁠`

    output.name.intern =

      `⁠NOT IN USE⁠`

    initial =

      `⁠4⁠`

    fixed =

      `⁠TRUE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 1⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

Model 'gompertz'.
  Properties:
    doc =

      `⁠gompertz distribution⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠FALSE⁠`

    link =

      `⁠default log neglog⁠`

    pdf =

      `⁠gompertz⁠`

  Number of hyperparmeters is 1.

  Hyperparameter 'theta'
    hyperid =

      `⁠105101⁠`

    name =

      `⁠shape⁠`

    short.name =

      `⁠alpha⁠`

    output.name.intern =

      `⁠alpha_intern for Gompertz⁠`

    output.name =

      `⁠alpha parameter for Gompertz⁠`

    initial =

      `⁠-1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 1⁠`

    to.theta =

      `⁠function(x, sc = 0.1) log(x) / sc⁠`

    from.theta =

      `⁠function(x, sc = 0.1) exp(sc * x)⁠`

Model 'gompertzsurv'.
  Properties:
    doc =

      `⁠gompertz distribution⁠`

    survival =

      `⁠TRUE⁠`

    discrete =

      `⁠FALSE⁠`

    link =

      `⁠default log neglog⁠`

    pdf =

      `⁠gompertz⁠`

  Number of hyperparmeters is 11.

  Hyperparameter 'theta1'
    hyperid =

      `⁠106101⁠`

    name =

      `⁠shape⁠`

    short.name =

      `⁠alpha⁠`

    output.name.intern =

      `⁠alpha_intern for Gompertz-surv⁠`

    output.name =

      `⁠alpha parameter for Gompertz-surv⁠`

    initial =

      `⁠-10⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 1⁠`

    to.theta =

      `⁠function(x, sc = 0.1) log(x) / sc⁠`

    from.theta =

      `⁠function(x, sc = 0.1) exp(sc * x)⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠106102⁠`

    name =

      `⁠beta1⁠`

    short.name =

      `⁠beta1⁠`

    output.name =

      `⁠beta1 for Gompertz-Cure⁠`

    output.name.intern =

      `⁠beta1 for Gompertz-Cure⁠`

    initial =

      `⁠-5⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠-4 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta3'
    hyperid =

      `⁠106103⁠`

    name =

      `⁠beta2⁠`

    short.name =

      `⁠beta2⁠`

    output.name =

      `⁠beta2 for Gompertz-Cure⁠`

    output.name.intern =

      `⁠beta2 for Gompertz-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta4'
    hyperid =

      `⁠106104⁠`

    name =

      `⁠beta3⁠`

    short.name =

      `⁠beta3⁠`

    output.name =

      `⁠beta3 for Gompertz-Cure⁠`

    output.name.intern =

      `⁠beta3 for Gompertz-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta5'
    hyperid =

      `⁠106105⁠`

    name =

      `⁠beta4⁠`

    short.name =

      `⁠beta4⁠`

    output.name =

      `⁠beta4 for Gompertz-Cure⁠`

    output.name.intern =

      `⁠beta4 for Gompertz-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta6'
    hyperid =

      `⁠106106⁠`

    name =

      `⁠beta5⁠`

    short.name =

      `⁠beta5⁠`

    output.name =

      `⁠beta5 for Gompertz-Cure⁠`

    output.name.intern =

      `⁠beta5 for Gompertz-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta7'
    hyperid =

      `⁠106107⁠`

    name =

      `⁠beta6⁠`

    short.name =

      `⁠beta6⁠`

    output.name =

      `⁠beta6 for Gompertz-Cure⁠`

    output.name.intern =

      `⁠beta6 for Gompertz-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta8'
    hyperid =

      `⁠106108⁠`

    name =

      `⁠beta7⁠`

    short.name =

      `⁠beta7⁠`

    output.name =

      `⁠beta7 for Gompertz-Cure⁠`

    output.name.intern =

      `⁠beta7 for Gompertz-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta9'
    hyperid =

      `⁠106109⁠`

    name =

      `⁠beta8⁠`

    short.name =

      `⁠beta8⁠`

    output.name =

      `⁠beta8 for Gompertz-Cure⁠`

    output.name.intern =

      `⁠beta8 for Gompertz-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta10'
    hyperid =

      `⁠106110⁠`

    name =

      `⁠beta9⁠`

    short.name =

      `⁠beta9⁠`

    output.name =

      `⁠beta9 for Gompertz-Cure⁠`

    output.name.intern =

      `⁠beta9 for Gompertz-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta11'
    hyperid =

      `⁠106111⁠`

    name =

      `⁠beta10⁠`

    short.name =

      `⁠beta10⁠`

    output.name =

      `⁠beta10 for Gompertz-Cure⁠`

    output.name.intern =

      `⁠beta10 for Gompertz-Cure⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 100⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

Model 'dgompertzsurv'.
  Properties:
    doc =

      `⁠destructive gompertz (survival) distribution⁠`

    experimental =

      `⁠TRUE⁠`

    survival =

      `⁠TRUE⁠`

    discrete =

      `⁠FALSE⁠`

    link =

      `⁠default log neglog⁠`

    pdf =

      `⁠dgompertz⁠`

  Number of hyperparmeters is 1.

  Hyperparameter 'theta'
    hyperid =

      `⁠108101⁠`

    name =

      `⁠shape⁠`

    short.name =

      `⁠alpha⁠`

    output.name.intern =

      `⁠alpha_intern for dGompertz⁠`

    output.name =

      `⁠alpha parameter for dGompertz⁠`

    initial =

      `⁠-1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠0 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

Model 'vm'.
  Properties:
    doc =

      `⁠von Mises circular distribution⁠`

    experimental =

      `⁠TRUE⁠`

    status =

      `⁠disabled⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠FALSE⁠`

    link =

      `⁠default circular tan identity⁠`

    pdf =

      `⁠vm⁠`

  Number of hyperparmeters is 1.

  Hyperparameter 'theta'
    hyperid =

      `⁠109101⁠`

    name =

      `⁠precision⁠`

    short.name =

      `⁠prec⁠`

    output.name.intern =

      `⁠prec_intern for vm⁠`

    output.name =

      `⁠precision parameter for vm⁠`

    initial =

      `⁠2⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 0.01⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

Model 'nvm'.
  Properties:
    doc =

      `⁠Normal approx of the von Mises circular distribution⁠`

    experimental =

      `⁠TRUE⁠`

    status =

      `⁠disabled⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠FALSE⁠`

    link =

      `⁠default circular tan identity⁠`

    pdf =

      `⁠vm⁠`

  Number of hyperparmeters is 1.

  Hyperparameter 'theta'
    hyperid =

      `⁠109201⁠`

    name =

      `⁠precision⁠`

    short.name =

      `⁠prec⁠`

    output.name.intern =

      `⁠prec_intern for nvm⁠`

    output.name =

      `⁠precision parameter for nvm⁠`

    initial =

      `⁠2⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 0.01⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

Model 'lavm'.
  Properties:
    doc =

      `⁠Link adjusted von Mises circular distribution⁠`

    experimental =

      `⁠TRUE⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠FALSE⁠`

    link =

      `⁠default circular tan identity⁠`

    pdf =

      `⁠lavm⁠`

  Number of hyperparmeters is 1.

  Hyperparameter 'theta'
    hyperid =

      `⁠109301⁠`

    name =

      `⁠precision⁠`

    short.name =

      `⁠prec⁠`

    output.name.intern =

      `⁠prec_intern for lavm⁠`

    output.name =

      `⁠precision parameter for lavm⁠`

    initial =

      `⁠2⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 0.01⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

Model 'cloglike'.
  Properties:
    doc =

      `⁠User-defined likelihood⁠`

    experimental =

      `⁠TRUE⁠`

    survival =

      `⁠FALSE⁠`

    discrete =

      `⁠FALSE⁠`

    link =

      `⁠default identity⁠`

    pdf =

      `⁠cloglike⁠`

  Number of hyperparmeters is 0.

### 'prior'

Valid models in this section are:

Model 'normal'.

  Number of parameters in the prior = 2

Model 'gaussian'.

  Number of parameters in the prior = 2

Model 'laplace'.

  Number of parameters in the prior = 2

Model 'linksnintercept'.

  Number of parameters in the prior = 2

Model 'wishart1d'.

  Number of parameters in the prior = 2

Model 'wishart2d'.

  Number of parameters in the prior = 4

Model 'wishart3d'.

  Number of parameters in the prior = 7

Model 'wishart4d'.

  Number of parameters in the prior = 11

Model 'wishart5d'.

  Number of parameters in the prior = 16

Model 'loggamma'.

  Number of parameters in the prior = 2

Model 'gamma'.

  Number of parameters in the prior = 2

Model 'pc.prw2.range'.

  Number of parameters in the prior = 4

Model 'minuslogsqrtruncnormal'.

  Number of parameters in the prior = 2

Model 'logtnormal'.

  Number of parameters in the prior = 2

Model 'logtgaussian'.

  Number of parameters in the prior = 2

Model 'flat'.

  Number of parameters in the prior = 0

Model 'logflat'.

  Number of parameters in the prior = 0

Model 'logiflat'.

  Number of parameters in the prior = 0

Model 'mvnorm'.

  Number of parameters in the prior = -1

Model 'pc.alphaw'.

  Number of parameters in the prior = 1

Model 'pc.ar'.

  Number of parameters in the prior = 1

Model 'dirichlet'.

  Number of parameters in the prior = 1

Model 'none'.

  Number of parameters in the prior = 0

Model 'invalid'.

  Number of parameters in the prior = 0

Model 'betacorrelation'.

  Number of parameters in the prior = 2

Model 'logitbeta'.

  Number of parameters in the prior = 2

Model 'pc.prec'.

  Number of parameters in the prior = 2

Model 'pc.dof'.

  Number of parameters in the prior = 2

Model 'pc.cor0'.

  Number of parameters in the prior = 2

Model 'pc.cor1'.

  Number of parameters in the prior = 2

Model 'pc.fgnh'.

  Number of parameters in the prior = 2

Model 'pc.spde.GA'.

  Number of parameters in the prior = 4

Model 'pc.matern'.

  Number of parameters in the prior = 3

Model 'pc.range'.

  Number of parameters in the prior = 2

Model 'pc.sn'.

  Number of parameters in the prior = 1

Model 'pc.gamma'.

  Number of parameters in the prior = 1

Model 'pc.mgamma'.

  Number of parameters in the prior = 1

Model 'pc.gammacount'.

  Number of parameters in the prior = 1

Model 'pc.gevtail'.

  Number of parameters in the prior = 3

Model 'pc.egptail'.

  Number of parameters in the prior = 3

Model 'pc'.

  Number of parameters in the prior = 2

Model 'ref.ar'.

  Number of parameters in the prior = 0

Model 'pom'.

  Number of parameters in the prior = 0

Model 'jeffreystdf'.

  Number of parameters in the prior = 0

Model 'wishartkd'.

  Number of parameters in the prior = 301

Model 'expression:'.

  Number of parameters in the prior = -1

Model 'table:'.

  Number of parameters in the prior = -1

Model 'rprior:'.

  Number of parameters in the prior = 0

### 'wrapper'

Valid models in this section are:

Model 'joint'.
  Properties:
    doc =

      `⁠(experimental)⁠`

    constr =

      `⁠FALSE⁠`

    nrow.ncol =

      `⁠FALSE⁠`

    augmented =

      `⁠FALSE⁠`

    aug.factor =

      `⁠1⁠`

    aug.constr =

      `⁠NULL⁠`

    n.div.by =

      `⁠NULL⁠`

    n.required =

      `⁠FALSE⁠`

    set.default.values =

      `⁠FALSE⁠`

    pdf =

      `⁠NA⁠`

  Number of hyperparmeters is 1.

  Hyperparameter 'theta'
    hyperid =

      `⁠102001⁠`

    name =

      `⁠log precision⁠`

    short.name =

      `⁠prec⁠`

    output.name =

      `⁠NOT IN USE⁠`

    output.name.intern =

      `⁠NOT IN USE⁠`

    initial =

      `⁠0⁠`

    fixed =

      `⁠TRUE⁠`

    prior =

      `⁠loggamma⁠`

    param =

      `⁠1 5e-05⁠`

    to.theta =

      `⁠function(x) log(x)⁠`

    from.theta =

      `⁠function(x) exp(x)⁠`

### 'lp.scale'

Valid models in this section are:

Model 'lp.scale'.
  Properties:
    pdf =

      `⁠lp.scale⁠`

  Number of hyperparmeters is 100.

  Hyperparameter 'theta1'
    hyperid =

      `⁠103001⁠`

    name =

      `⁠beta1⁠`

    short.name =

      `⁠b1⁠`

    output.name =

      `⁠beta[1] for lp_scale⁠`

    output.name.intern =

      `⁠beta[1] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta2'
    hyperid =

      `⁠103002⁠`

    name =

      `⁠beta2⁠`

    short.name =

      `⁠b2⁠`

    output.name =

      `⁠beta[2] for lp_scale⁠`

    output.name.intern =

      `⁠beta[2] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta3'
    hyperid =

      `⁠103003⁠`

    name =

      `⁠beta3⁠`

    short.name =

      `⁠b3⁠`

    output.name =

      `⁠beta[3] for lp_scale⁠`

    output.name.intern =

      `⁠beta[3] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta4'
    hyperid =

      `⁠103004⁠`

    name =

      `⁠beta4⁠`

    short.name =

      `⁠b4⁠`

    output.name =

      `⁠beta[4] for lp_scale⁠`

    output.name.intern =

      `⁠beta[4] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta5'
    hyperid =

      `⁠103005⁠`

    name =

      `⁠beta5⁠`

    short.name =

      `⁠b5⁠`

    output.name =

      `⁠beta[5] for lp_scale⁠`

    output.name.intern =

      `⁠beta[5] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta6'
    hyperid =

      `⁠103006⁠`

    name =

      `⁠beta6⁠`

    short.name =

      `⁠b6⁠`

    output.name =

      `⁠beta[6] for lp_scale⁠`

    output.name.intern =

      `⁠beta[6] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta7'
    hyperid =

      `⁠103007⁠`

    name =

      `⁠beta7⁠`

    short.name =

      `⁠b7⁠`

    output.name =

      `⁠beta[7] for lp_scale⁠`

    output.name.intern =

      `⁠beta[7] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta8'
    hyperid =

      `⁠103008⁠`

    name =

      `⁠beta8⁠`

    short.name =

      `⁠b8⁠`

    output.name =

      `⁠beta[8] for lp_scale⁠`

    output.name.intern =

      `⁠beta[8] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta9'
    hyperid =

      `⁠103009⁠`

    name =

      `⁠beta9⁠`

    short.name =

      `⁠b9⁠`

    output.name =

      `⁠beta[9] for lp_scale⁠`

    output.name.intern =

      `⁠beta[9] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta10'
    hyperid =

      `⁠103010⁠`

    name =

      `⁠beta10⁠`

    short.name =

      `⁠b10⁠`

    output.name =

      `⁠beta[10] for lp_scale⁠`

    output.name.intern =

      `⁠beta[10] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta11'
    hyperid =

      `⁠103011⁠`

    name =

      `⁠beta11⁠`

    short.name =

      `⁠b11⁠`

    output.name =

      `⁠beta[11] for lp_scale⁠`

    output.name.intern =

      `⁠beta[11] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta12'
    hyperid =

      `⁠103012⁠`

    name =

      `⁠beta12⁠`

    short.name =

      `⁠b12⁠`

    output.name =

      `⁠beta[12] for lp_scale⁠`

    output.name.intern =

      `⁠beta[12] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta13'
    hyperid =

      `⁠103013⁠`

    name =

      `⁠beta13⁠`

    short.name =

      `⁠b13⁠`

    output.name =

      `⁠beta[13] for lp_scale⁠`

    output.name.intern =

      `⁠beta[13] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta14'
    hyperid =

      `⁠103014⁠`

    name =

      `⁠beta14⁠`

    short.name =

      `⁠b14⁠`

    output.name =

      `⁠beta[14] for lp_scale⁠`

    output.name.intern =

      `⁠beta[14] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta15'
    hyperid =

      `⁠103015⁠`

    name =

      `⁠beta15⁠`

    short.name =

      `⁠b15⁠`

    output.name =

      `⁠beta[15] for lp_scale⁠`

    output.name.intern =

      `⁠beta[15] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta16'
    hyperid =

      `⁠103016⁠`

    name =

      `⁠beta16⁠`

    short.name =

      `⁠b16⁠`

    output.name =

      `⁠beta[16] for lp_scale⁠`

    output.name.intern =

      `⁠beta[16] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta17'
    hyperid =

      `⁠103017⁠`

    name =

      `⁠beta17⁠`

    short.name =

      `⁠b17⁠`

    output.name =

      `⁠beta[17] for lp_scale⁠`

    output.name.intern =

      `⁠beta[17] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta18'
    hyperid =

      `⁠103018⁠`

    name =

      `⁠beta18⁠`

    short.name =

      `⁠b18⁠`

    output.name =

      `⁠beta[18] for lp_scale⁠`

    output.name.intern =

      `⁠beta[18] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta19'
    hyperid =

      `⁠103019⁠`

    name =

      `⁠beta19⁠`

    short.name =

      `⁠b19⁠`

    output.name =

      `⁠beta[19] for lp_scale⁠`

    output.name.intern =

      `⁠beta[19] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta20'
    hyperid =

      `⁠103020⁠`

    name =

      `⁠beta20⁠`

    short.name =

      `⁠b20⁠`

    output.name =

      `⁠beta[20] for lp_scale⁠`

    output.name.intern =

      `⁠beta[20] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta21'
    hyperid =

      `⁠103021⁠`

    name =

      `⁠beta21⁠`

    short.name =

      `⁠b21⁠`

    output.name =

      `⁠beta[21] for lp_scale⁠`

    output.name.intern =

      `⁠beta[21] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta22'
    hyperid =

      `⁠103022⁠`

    name =

      `⁠beta22⁠`

    short.name =

      `⁠b22⁠`

    output.name =

      `⁠beta[22] for lp_scale⁠`

    output.name.intern =

      `⁠beta[22] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta23'
    hyperid =

      `⁠103023⁠`

    name =

      `⁠beta23⁠`

    short.name =

      `⁠b23⁠`

    output.name =

      `⁠beta[23] for lp_scale⁠`

    output.name.intern =

      `⁠beta[23] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta24'
    hyperid =

      `⁠103024⁠`

    name =

      `⁠beta24⁠`

    short.name =

      `⁠b24⁠`

    output.name =

      `⁠beta[24] for lp_scale⁠`

    output.name.intern =

      `⁠beta[24] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta25'
    hyperid =

      `⁠103025⁠`

    name =

      `⁠beta25⁠`

    short.name =

      `⁠b25⁠`

    output.name =

      `⁠beta[25] for lp_scale⁠`

    output.name.intern =

      `⁠beta[25] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta26'
    hyperid =

      `⁠103026⁠`

    name =

      `⁠beta26⁠`

    short.name =

      `⁠b26⁠`

    output.name =

      `⁠beta[26] for lp_scale⁠`

    output.name.intern =

      `⁠beta[26] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta27'
    hyperid =

      `⁠103027⁠`

    name =

      `⁠beta27⁠`

    short.name =

      `⁠b27⁠`

    output.name =

      `⁠beta[27] for lp_scale⁠`

    output.name.intern =

      `⁠beta[27] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta28'
    hyperid =

      `⁠103028⁠`

    name =

      `⁠beta28⁠`

    short.name =

      `⁠b28⁠`

    output.name =

      `⁠beta[28] for lp_scale⁠`

    output.name.intern =

      `⁠beta[28] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta29'
    hyperid =

      `⁠103029⁠`

    name =

      `⁠beta29⁠`

    short.name =

      `⁠b29⁠`

    output.name =

      `⁠beta[29] for lp_scale⁠`

    output.name.intern =

      `⁠beta[29] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta30'
    hyperid =

      `⁠103030⁠`

    name =

      `⁠beta30⁠`

    short.name =

      `⁠b30⁠`

    output.name =

      `⁠beta[30] for lp_scale⁠`

    output.name.intern =

      `⁠beta[30] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta31'
    hyperid =

      `⁠103031⁠`

    name =

      `⁠beta31⁠`

    short.name =

      `⁠b31⁠`

    output.name =

      `⁠beta[31] for lp_scale⁠`

    output.name.intern =

      `⁠beta[31] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta32'
    hyperid =

      `⁠103032⁠`

    name =

      `⁠beta32⁠`

    short.name =

      `⁠b32⁠`

    output.name =

      `⁠beta[32] for lp_scale⁠`

    output.name.intern =

      `⁠beta[32] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta33'
    hyperid =

      `⁠103033⁠`

    name =

      `⁠beta33⁠`

    short.name =

      `⁠b33⁠`

    output.name =

      `⁠beta[33] for lp_scale⁠`

    output.name.intern =

      `⁠beta[33] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta34'
    hyperid =

      `⁠103034⁠`

    name =

      `⁠beta34⁠`

    short.name =

      `⁠b34⁠`

    output.name =

      `⁠beta[34] for lp_scale⁠`

    output.name.intern =

      `⁠beta[34] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta35'
    hyperid =

      `⁠103035⁠`

    name =

      `⁠beta35⁠`

    short.name =

      `⁠b35⁠`

    output.name =

      `⁠beta[35] for lp_scale⁠`

    output.name.intern =

      `⁠beta[35] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta36'
    hyperid =

      `⁠103036⁠`

    name =

      `⁠beta36⁠`

    short.name =

      `⁠b36⁠`

    output.name =

      `⁠beta[36] for lp_scale⁠`

    output.name.intern =

      `⁠beta[36] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta37'
    hyperid =

      `⁠103037⁠`

    name =

      `⁠beta37⁠`

    short.name =

      `⁠b37⁠`

    output.name =

      `⁠beta[37] for lp_scale⁠`

    output.name.intern =

      `⁠beta[37] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta38'
    hyperid =

      `⁠103038⁠`

    name =

      `⁠beta38⁠`

    short.name =

      `⁠b38⁠`

    output.name =

      `⁠beta[38] for lp_scale⁠`

    output.name.intern =

      `⁠beta[38] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta39'
    hyperid =

      `⁠103039⁠`

    name =

      `⁠beta39⁠`

    short.name =

      `⁠b39⁠`

    output.name =

      `⁠beta[39] for lp_scale⁠`

    output.name.intern =

      `⁠beta[39] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta40'
    hyperid =

      `⁠103040⁠`

    name =

      `⁠beta40⁠`

    short.name =

      `⁠b40⁠`

    output.name =

      `⁠beta[40] for lp_scale⁠`

    output.name.intern =

      `⁠beta[40] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta41'
    hyperid =

      `⁠103041⁠`

    name =

      `⁠beta41⁠`

    short.name =

      `⁠b41⁠`

    output.name =

      `⁠beta[41] for lp_scale⁠`

    output.name.intern =

      `⁠beta[41] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta42'
    hyperid =

      `⁠103042⁠`

    name =

      `⁠beta42⁠`

    short.name =

      `⁠b42⁠`

    output.name =

      `⁠beta[42] for lp_scale⁠`

    output.name.intern =

      `⁠beta[42] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta43'
    hyperid =

      `⁠103043⁠`

    name =

      `⁠beta43⁠`

    short.name =

      `⁠b43⁠`

    output.name =

      `⁠beta[43] for lp_scale⁠`

    output.name.intern =

      `⁠beta[43] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta44'
    hyperid =

      `⁠103044⁠`

    name =

      `⁠beta44⁠`

    short.name =

      `⁠b44⁠`

    output.name =

      `⁠beta[44] for lp_scale⁠`

    output.name.intern =

      `⁠beta[44] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta45'
    hyperid =

      `⁠103045⁠`

    name =

      `⁠beta45⁠`

    short.name =

      `⁠b45⁠`

    output.name =

      `⁠beta[45] for lp_scale⁠`

    output.name.intern =

      `⁠beta[45] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta46'
    hyperid =

      `⁠103046⁠`

    name =

      `⁠beta46⁠`

    short.name =

      `⁠b46⁠`

    output.name =

      `⁠beta[46] for lp_scale⁠`

    output.name.intern =

      `⁠beta[46] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta47'
    hyperid =

      `⁠103047⁠`

    name =

      `⁠beta47⁠`

    short.name =

      `⁠b47⁠`

    output.name =

      `⁠beta[47] for lp_scale⁠`

    output.name.intern =

      `⁠beta[47] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta48'
    hyperid =

      `⁠103048⁠`

    name =

      `⁠beta48⁠`

    short.name =

      `⁠b48⁠`

    output.name =

      `⁠beta[48] for lp_scale⁠`

    output.name.intern =

      `⁠beta[48] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta49'
    hyperid =

      `⁠103049⁠`

    name =

      `⁠beta49⁠`

    short.name =

      `⁠b49⁠`

    output.name =

      `⁠beta[49] for lp_scale⁠`

    output.name.intern =

      `⁠beta[49] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta50'
    hyperid =

      `⁠103050⁠`

    name =

      `⁠beta50⁠`

    short.name =

      `⁠b50⁠`

    output.name =

      `⁠beta[50] for lp_scale⁠`

    output.name.intern =

      `⁠beta[50] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta51'
    hyperid =

      `⁠103051⁠`

    name =

      `⁠beta51⁠`

    short.name =

      `⁠b51⁠`

    output.name =

      `⁠beta[51] for lp_scale⁠`

    output.name.intern =

      `⁠beta[51] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta52'
    hyperid =

      `⁠103052⁠`

    name =

      `⁠beta52⁠`

    short.name =

      `⁠b52⁠`

    output.name =

      `⁠beta[52] for lp_scale⁠`

    output.name.intern =

      `⁠beta[52] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta53'
    hyperid =

      `⁠103053⁠`

    name =

      `⁠beta53⁠`

    short.name =

      `⁠b53⁠`

    output.name =

      `⁠beta[53] for lp_scale⁠`

    output.name.intern =

      `⁠beta[53] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta54'
    hyperid =

      `⁠103054⁠`

    name =

      `⁠beta54⁠`

    short.name =

      `⁠b54⁠`

    output.name =

      `⁠beta[54] for lp_scale⁠`

    output.name.intern =

      `⁠beta[54] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta55'
    hyperid =

      `⁠103055⁠`

    name =

      `⁠beta55⁠`

    short.name =

      `⁠b55⁠`

    output.name =

      `⁠beta[55] for lp_scale⁠`

    output.name.intern =

      `⁠beta[55] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta56'
    hyperid =

      `⁠103056⁠`

    name =

      `⁠beta56⁠`

    short.name =

      `⁠b56⁠`

    output.name =

      `⁠beta[56] for lp_scale⁠`

    output.name.intern =

      `⁠beta[56] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta57'
    hyperid =

      `⁠103057⁠`

    name =

      `⁠beta57⁠`

    short.name =

      `⁠b57⁠`

    output.name =

      `⁠beta[57] for lp_scale⁠`

    output.name.intern =

      `⁠beta[57] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta58'
    hyperid =

      `⁠103058⁠`

    name =

      `⁠beta58⁠`

    short.name =

      `⁠b58⁠`

    output.name =

      `⁠beta[58] for lp_scale⁠`

    output.name.intern =

      `⁠beta[58] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta59'
    hyperid =

      `⁠103059⁠`

    name =

      `⁠beta59⁠`

    short.name =

      `⁠b59⁠`

    output.name =

      `⁠beta[59] for lp_scale⁠`

    output.name.intern =

      `⁠beta[59] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta60'
    hyperid =

      `⁠103060⁠`

    name =

      `⁠beta60⁠`

    short.name =

      `⁠b60⁠`

    output.name =

      `⁠beta[60] for lp_scale⁠`

    output.name.intern =

      `⁠beta[60] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta61'
    hyperid =

      `⁠103061⁠`

    name =

      `⁠beta61⁠`

    short.name =

      `⁠b61⁠`

    output.name =

      `⁠beta[61] for lp_scale⁠`

    output.name.intern =

      `⁠beta[61] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta62'
    hyperid =

      `⁠103062⁠`

    name =

      `⁠beta62⁠`

    short.name =

      `⁠b62⁠`

    output.name =

      `⁠beta[62] for lp_scale⁠`

    output.name.intern =

      `⁠beta[62] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta63'
    hyperid =

      `⁠103063⁠`

    name =

      `⁠beta63⁠`

    short.name =

      `⁠b63⁠`

    output.name =

      `⁠beta[63] for lp_scale⁠`

    output.name.intern =

      `⁠beta[63] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta64'
    hyperid =

      `⁠103064⁠`

    name =

      `⁠beta64⁠`

    short.name =

      `⁠b64⁠`

    output.name =

      `⁠beta[64] for lp_scale⁠`

    output.name.intern =

      `⁠beta[64] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta65'
    hyperid =

      `⁠103065⁠`

    name =

      `⁠beta65⁠`

    short.name =

      `⁠b65⁠`

    output.name =

      `⁠beta[65] for lp_scale⁠`

    output.name.intern =

      `⁠beta[65] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta66'
    hyperid =

      `⁠103066⁠`

    name =

      `⁠beta66⁠`

    short.name =

      `⁠b66⁠`

    output.name =

      `⁠beta[66] for lp_scale⁠`

    output.name.intern =

      `⁠beta[66] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta67'
    hyperid =

      `⁠103067⁠`

    name =

      `⁠beta67⁠`

    short.name =

      `⁠b67⁠`

    output.name =

      `⁠beta[67] for lp_scale⁠`

    output.name.intern =

      `⁠beta[67] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta68'
    hyperid =

      `⁠103068⁠`

    name =

      `⁠beta68⁠`

    short.name =

      `⁠b68⁠`

    output.name =

      `⁠beta[68] for lp_scale⁠`

    output.name.intern =

      `⁠beta[68] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta69'
    hyperid =

      `⁠103069⁠`

    name =

      `⁠beta69⁠`

    short.name =

      `⁠b69⁠`

    output.name =

      `⁠beta[69] for lp_scale⁠`

    output.name.intern =

      `⁠beta[69] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta70'
    hyperid =

      `⁠103070⁠`

    name =

      `⁠beta70⁠`

    short.name =

      `⁠b70⁠`

    output.name =

      `⁠beta[70] for lp_scale⁠`

    output.name.intern =

      `⁠beta[70] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta71'
    hyperid =

      `⁠103071⁠`

    name =

      `⁠beta71⁠`

    short.name =

      `⁠b71⁠`

    output.name =

      `⁠beta[71] for lp_scale⁠`

    output.name.intern =

      `⁠beta[71] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta72'
    hyperid =

      `⁠103072⁠`

    name =

      `⁠beta72⁠`

    short.name =

      `⁠b72⁠`

    output.name =

      `⁠beta[72] for lp_scale⁠`

    output.name.intern =

      `⁠beta[72] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta73'
    hyperid =

      `⁠103073⁠`

    name =

      `⁠beta73⁠`

    short.name =

      `⁠b73⁠`

    output.name =

      `⁠beta[73] for lp_scale⁠`

    output.name.intern =

      `⁠beta[73] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta74'
    hyperid =

      `⁠103074⁠`

    name =

      `⁠beta74⁠`

    short.name =

      `⁠b74⁠`

    output.name =

      `⁠beta[74] for lp_scale⁠`

    output.name.intern =

      `⁠beta[74] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta75'
    hyperid =

      `⁠103075⁠`

    name =

      `⁠beta75⁠`

    short.name =

      `⁠b75⁠`

    output.name =

      `⁠beta[75] for lp_scale⁠`

    output.name.intern =

      `⁠beta[75] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta76'
    hyperid =

      `⁠103076⁠`

    name =

      `⁠beta76⁠`

    short.name =

      `⁠b76⁠`

    output.name =

      `⁠beta[76] for lp_scale⁠`

    output.name.intern =

      `⁠beta[76] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta77'
    hyperid =

      `⁠103077⁠`

    name =

      `⁠beta77⁠`

    short.name =

      `⁠b77⁠`

    output.name =

      `⁠beta[77] for lp_scale⁠`

    output.name.intern =

      `⁠beta[77] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta78'
    hyperid =

      `⁠103078⁠`

    name =

      `⁠beta78⁠`

    short.name =

      `⁠b78⁠`

    output.name =

      `⁠beta[78] for lp_scale⁠`

    output.name.intern =

      `⁠beta[78] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta79'
    hyperid =

      `⁠103079⁠`

    name =

      `⁠beta79⁠`

    short.name =

      `⁠b79⁠`

    output.name =

      `⁠beta[79] for lp_scale⁠`

    output.name.intern =

      `⁠beta[79] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta80'
    hyperid =

      `⁠103080⁠`

    name =

      `⁠beta80⁠`

    short.name =

      `⁠b80⁠`

    output.name =

      `⁠beta[80] for lp_scale⁠`

    output.name.intern =

      `⁠beta[80] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta81'
    hyperid =

      `⁠103081⁠`

    name =

      `⁠beta81⁠`

    short.name =

      `⁠b81⁠`

    output.name =

      `⁠beta[81] for lp_scale⁠`

    output.name.intern =

      `⁠beta[81] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta82'
    hyperid =

      `⁠103082⁠`

    name =

      `⁠beta82⁠`

    short.name =

      `⁠b82⁠`

    output.name =

      `⁠beta[82] for lp_scale⁠`

    output.name.intern =

      `⁠beta[82] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta83'
    hyperid =

      `⁠103083⁠`

    name =

      `⁠beta83⁠`

    short.name =

      `⁠b83⁠`

    output.name =

      `⁠beta[83] for lp_scale⁠`

    output.name.intern =

      `⁠beta[83] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta84'
    hyperid =

      `⁠103084⁠`

    name =

      `⁠beta84⁠`

    short.name =

      `⁠b84⁠`

    output.name =

      `⁠beta[84] for lp_scale⁠`

    output.name.intern =

      `⁠beta[84] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta85'
    hyperid =

      `⁠103085⁠`

    name =

      `⁠beta85⁠`

    short.name =

      `⁠b85⁠`

    output.name =

      `⁠beta[85] for lp_scale⁠`

    output.name.intern =

      `⁠beta[85] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta86'
    hyperid =

      `⁠103086⁠`

    name =

      `⁠beta86⁠`

    short.name =

      `⁠b86⁠`

    output.name =

      `⁠beta[86] for lp_scale⁠`

    output.name.intern =

      `⁠beta[86] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta87'
    hyperid =

      `⁠103087⁠`

    name =

      `⁠beta87⁠`

    short.name =

      `⁠b87⁠`

    output.name =

      `⁠beta[87] for lp_scale⁠`

    output.name.intern =

      `⁠beta[87] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta88'
    hyperid =

      `⁠103088⁠`

    name =

      `⁠beta88⁠`

    short.name =

      `⁠b88⁠`

    output.name =

      `⁠beta[88] for lp_scale⁠`

    output.name.intern =

      `⁠beta[88] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta89'
    hyperid =

      `⁠103089⁠`

    name =

      `⁠beta89⁠`

    short.name =

      `⁠b89⁠`

    output.name =

      `⁠beta[89] for lp_scale⁠`

    output.name.intern =

      `⁠beta[89] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta90'
    hyperid =

      `⁠103090⁠`

    name =

      `⁠beta90⁠`

    short.name =

      `⁠b90⁠`

    output.name =

      `⁠beta[90] for lp_scale⁠`

    output.name.intern =

      `⁠beta[90] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta91'
    hyperid =

      `⁠103091⁠`

    name =

      `⁠beta91⁠`

    short.name =

      `⁠b91⁠`

    output.name =

      `⁠beta[91] for lp_scale⁠`

    output.name.intern =

      `⁠beta[91] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta92'
    hyperid =

      `⁠103092⁠`

    name =

      `⁠beta92⁠`

    short.name =

      `⁠b92⁠`

    output.name =

      `⁠beta[92] for lp_scale⁠`

    output.name.intern =

      `⁠beta[92] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta93'
    hyperid =

      `⁠103093⁠`

    name =

      `⁠beta93⁠`

    short.name =

      `⁠b93⁠`

    output.name =

      `⁠beta[93] for lp_scale⁠`

    output.name.intern =

      `⁠beta[93] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta94'
    hyperid =

      `⁠103094⁠`

    name =

      `⁠beta94⁠`

    short.name =

      `⁠b94⁠`

    output.name =

      `⁠beta[94] for lp_scale⁠`

    output.name.intern =

      `⁠beta[94] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta95'
    hyperid =

      `⁠103095⁠`

    name =

      `⁠beta95⁠`

    short.name =

      `⁠b95⁠`

    output.name =

      `⁠beta[95] for lp_scale⁠`

    output.name.intern =

      `⁠beta[95] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta96'
    hyperid =

      `⁠103096⁠`

    name =

      `⁠beta96⁠`

    short.name =

      `⁠b96⁠`

    output.name =

      `⁠beta[96] for lp_scale⁠`

    output.name.intern =

      `⁠beta[96] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta97'
    hyperid =

      `⁠103097⁠`

    name =

      `⁠beta97⁠`

    short.name =

      `⁠b97⁠`

    output.name =

      `⁠beta[97] for lp_scale⁠`

    output.name.intern =

      `⁠beta[97] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta98'
    hyperid =

      `⁠103098⁠`

    name =

      `⁠beta98⁠`

    short.name =

      `⁠b98⁠`

    output.name =

      `⁠beta[98] for lp_scale⁠`

    output.name.intern =

      `⁠beta[98] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta99'
    hyperid =

      `⁠103099⁠`

    name =

      `⁠beta99⁠`

    short.name =

      `⁠b99⁠`

    output.name =

      `⁠beta[99] for lp_scale⁠`

    output.name.intern =

      `⁠beta[99] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

  Hyperparameter 'theta100'
    hyperid =

      `⁠103100⁠`

    name =

      `⁠beta100⁠`

    short.name =

      `⁠b100⁠`

    output.name =

      `⁠beta[100] for lp_scale⁠`

    output.name.intern =

      `⁠beta[100] for lp_scale⁠`

    initial =

      `⁠1⁠`

    fixed =

      `⁠FALSE⁠`

    prior =

      `⁠normal⁠`

    param =

      `⁠1 10⁠`

    to.theta =

      `⁠function(x) x⁠`

    from.theta =

      `⁠function(x) x⁠`

### Examples

    ## How to set hyperparameters to pass as the argument 'hyper'. This
    ## format is compatible with the old style (using 'initial', 'fixed',
    ## 'prior', 'param'), but the new style using 'hyper' takes precedence
    ## over the old style. The two styles can also be mixed. The old style
    ## might be removed from the code in the future...

    ## Only a subset need to be given
    hyper <- list(theta = list(initial = 2))
    ## The `name' can be used instead of 'theta', or 'theta1', 'theta2',...
    hyper <- list(precision = list(initial = 2))
    hyper <- list(precision = list(prior = "flat", param = numeric(0)))
    hyper <- list(theta2 = list(initial = 3), theta1 = list(prior = "gaussian"))
    ## The 'short.name' can be used instead of 'name'
    hyper <- list(rho = list(param = c(0, 1)))

[Package INLA version 26.08.22 Index]