prec.inla

Define the prec method for an inla output object

Contain code to work with a C struct, in short
cgeneric, to define a Gaussian Markov random (GMRF) model.
The cgeneric contain code to specify GMRF elements such as
the graph and the precision matrix, and also the initial and
prior for its parameters, useful for model inference.
It can be accessed from a C program and is the recommended
way to implement new GMRF models in the 'INLA' package
(<https://www.r-inla.org>).
The 'INLAtools' implement functions to evaluate
each one of the model specifications from R.
The implemented functionalities leverage the use
of 'cgeneric' models and provide a way to debug
the code as well to work with the prior for the
model parameters and to sample from it.
A very useful functionality is the Kronecker product method
that creates a new model from multiple cgeneric models.
It also works with the rgeneric, the R version of the
cgeneric intended to easy try implementation of new GMRF models.
The Kronecker between two cgeneric models was used in
Sterrantino et. al. (2024) <doi:10.1007/s10260-025-00788-y>,
and can be used to build the spatio-temporal intrinsic interaction
models for what the needed constraints are automatically set.

Elias Teixeira Krainski

INLAtools

Functionalities for the 'INLA' Package

Finn Lindgren

Haavard Rue’

prec.inla function

<dl><dt>model</dt>
<dd>an inla output</dd>
<dt>...</dt>
<dd>used to pass the 'prior' argument,
as logical (default is TRUE) to indicate if it is
to retrieve the prior or the posterior precision.</dd></dl>

Arguments

Define the prec method for an inla output object — prec.inla

<dl>

<dt>model</dt>
<dd>an inla output</dd>


<dt>...</dt>
<dd>used to pass the 'prior' argument,
as logical (default is TRUE) to indicate if it is
to retrieve the prior or the posterior precision.</dd>

</dl>

prec.inla: Define the prec method for an inla output object

Description

Usage

Arguments

Details