Package: INLAtools 0.1.5.908

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 required data to specify GMRF elements such as the graph and the precision matrix, as well hyper-parameters definition, such as initial values and the prior, which are 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>). We also provide access from R, useful for code debug and evaluate the prior for multiple parameter sets. The implemented functionalities leverage the use of 'cgeneric' models. In order to illustrate it, a model named `generic0` is included. It can be used to implement intrinsic models and scale it by default, as proposed in Sørbye & Rue (2014) <doi:10.1016/j.spasta.2013.06.004>, as well defining 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 before making it for production. The constraints of a Kronecker between two cgeneric models, such as spatio-temporal intrinsic interaction models, see Knorr-Held (2000) <doi:10.1002/1097-0258%2820000915/30%2919%3A17/18%3C2555%3A%3AAID-SIM587%3E3.0.CO%3B2-%23>, are automatically set, as shown in the example at <https://github.com/eliaskrainski/INLAtools>.

Authors:Elias Teixeira Krainski [cre, aut, cph], Finn Lindgren [aut], Haavard Rue’ [aut]