Bayesian Multivariate Spatial Models for Lattice Data with INLA
Computation
2020-05-07 v2
Abstract
The INLAMSM package for the R programming language provides a collection of multivariate spatial models for lattice data that can be used with package INLA for Bayesian inference. The multivariate spatial models include different structures to model the spatial variation of the variables and the between-variables variability. In this way, fitting multivariate spatial models becomes faster and easier. The use of the different models included in the package is illustrated using two different datasets: the well-known North Carolina SIDS data and mortality by three causes of death in Comunidad Valenciana (Spain).
Cite
@article{arxiv.1909.10804,
title = {Bayesian Multivariate Spatial Models for Lattice Data with INLA},
author = {Francisco Palmi-Perales and Virgilio Gomez-Rubio and Miguel A. Martinez-Beneito},
journal= {arXiv preprint arXiv:1909.10804},
year = {2020}
}