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.
Documentation:
Downloads:
Reverse dependencies:
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[cre, aut,
cph],
Finn Lindgren