Name of the covariate and, possibly of the weights vector. NB: order counts!!!! The first specified term is the covariate and the second one is the vector of weights (which can be negative).

A string indicating the chosen model. The default is iid. See names(inla.models()$latent) for a list of possible alternatives and inla.doc() for detailed docs.

The name of the model-component to copy

The name of the model-component to smooth-copy (where the copy-function is a spline)

Can be used with copy="..". same.as="A" says that this copy should use the same scaling parameter as another copy "A"

An optional argument which defines the dimension of the model if this is different from length(sort(unique(covariate)))

Number of replications, if not given, then nrep=max(replications)

A vector of which replications to use.

Number of groups, if not given, then ngroup=max(group)

A vector of which groups to use.

Controls the use of group

Controls the use of scopy

Specification of the hyperparameter, fixed or random, initial values, priors and its parameters. See ?inla.models for the list of hyparameters for each model and its default options or use inla.doc() for detailed info on the family and supported prior distributions.

THIS OPTION IS OBSOLETE, DO NOT USE

THIS OPTION IS OBSOLETE, DO NOT USE

THIS OPTION IS OBSOLETE, DO NOT USE

THIS OPTION IS OBSOLETE; DO NOT USE

Length of the seasonal component for model="seasonal"

A boolean variable indicating whater to set a sum to 0 constraint on the term. By default the sum to 0 constraint is imposed on all intrinsic models ("iid","rw1","rw1","besag", etc..).

This argument defines extra linear constraints. The argument is a list with two elements, a matrix A and a vector e, which defines the extra constraint Ax = e; for example extraconstr = list(A = A, e=e). The number of columns of A must correspond to the length of this f-model. Note that this constraint comes additional to the sum-to-zero constraint defined if constr = TRUE.

An optional vector giving all values assumed by the covariate for which we want estimated the effect. It must be a numeric vector, a vector of factors or NULL.

A boolean specifying wheather the model is cyclical. Only valid for "rw1" and "rw2" models, is cyclic=T then the sum to 0 constraint is removed. For the correct form of the grah file see Martino and Rue (2008).

An extra constant added to the diagonal of the precision matrix to prevent numerical issues.

Defines the graph-object either as a file with a graph-description, an inla.graph-object, or as a (sparse) symmetric matrix .

THIS OPTION IS OBSOLETE, DO NOT USE

THIS OPTION IS OBSOLETE, DO NOT USE

A vector of maximum 10 quantiles, p(0), p(1),\dots to compute for each posterior marginal. The function returns, for each posterior marginal, the values x(0), x(1),\dots such that

\mbox{Prob}(X<x(p))=p

The specification of the precision matrix for the generic, generic3 or z models (up to a scaling constant). Cmatrix is either a (dense) matrix, a matrix created using Matrix::sparseMatrix(), or a filename which stores the non-zero elements of Cmatrix, in three columns: i, j and Qij. In case of the generic3 model, it is a list of such specifications.

A number defining the rank deficiency of the model, with sum-to-zero constraint and possible extra-constraints taken into account. See details.

The matrix for the z-model

Number of rows for 2d-models

Number of columns for 2d-models

Smoothing parameter for the Matern2d-model, possible values are c(0, 1, 2, 3)

The boundary conditions for model rw2d, 0 means use the correct subspace (default), while 1 means condition on 0's outside

Internal use only

Internal use only

Internal use only

Internal use only

Internal use only

Prior mean for model="linear"

Prior precision for model="linear"

A boolean variable indicating whether the marginal posterior distribution for the nodes in the f() model should be computed or not. This is usefull for large models where we are only interested in some posterior marginals.

Internal use only

The precision for the artificial noise added when creating a copy of a model and others.

A vector of size two giving the lower and upper range for the scaling parameter beta in the model COPY, CLINEAR, MEC and MEB. If low = high then the identity mapping is used.

If TRUE (default), adjust some of the models (currently: besag, bym, bym2 and besag2) if the number of connected components in graph is larger than 1. If FALSE, do nothing.

Defines the order of the model: for model ar this defines the order p, in AR(p). Not used for other models at the time being.

A scaling vector. Its meaning depends on the model.

A object of class inla.rgeneric which defines the model. (EXPERIMENTAL!)

A object of class inla.cgeneric which defines the model. (EXPERIMENTAL!)

Logical. If TRUE then scale the RW1 and RW2 and BESAG and BYM and BESAG2 and RW2D models so the their (generlized) variance is 1. Default value is inla.getOption("scale.model.default")

Required arguments to the model="slm"; see the documentation for further details.

Required arguments to the model="ar1c"; see the documentation for further details.

A list with the subject (factor), strata (factor) and covariates (numeric) for the intslope model; see the documentation for further details,

Add this model component to the list of nodes to be used for the (potential) vb correction? If TRUE do, and do not if FALSE. Can also be a vector of nodes to add in the correction-set.

A matrix with locations for the model dmatern. This also defines n.

Enable local debug output

Local A-matrix (experimental and in development, do not use)