INLAtools - Functionalities for the 'INLA' Package
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. The `generic0` can be used
to implement intrinsic models with the scaling as proposed in
Sørbye & Rue (2014) <doi:10.1016/j.spasta.2013.06.004>, and the
required constraints. 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
where each one needs a constraint, such as spatio-temporal
intrinsic interaction models, the needed constraints are
automatically set.
