| 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-06- 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-04- 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-04- 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 '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- 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- 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- 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- status =
experimental- 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 '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 'binomialmix'.
-
- Properties:
-
- doc =
Binomial mixture- status =
experimental- 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 '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 '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- status =
experimental- 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 =
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 =
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- status =
experimental- 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- status =
experimental- 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- status =
experimental
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- status =
experimental
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- status =
experimental
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- status =
experimental- 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- survival =
FALSE- discrete =
FALSE- link =
default circular tan tan.pi 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)
'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 '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)))