Published by the Foundation for Open Access Statistics Editors-in-chief: Bettina Grün, Torsten Hothorn, Rebecca Killick, Edzer Pebesma, Achim Zeileis    ISSN 1548-7660; CODEN JSSOBK
Authors: Francisco Palmí-Perales, Virgilio Gómez-Rubio, Miguel A. Martinez-Beneito
Title: Bayesian Multivariate Spatial Models for Lattice Data with INLA
Abstract: The INLAMSM package for the R programming language provides a collection of multivariate spatial models for lattice data that can be used with the INLA package for Bayesian inference. The multivariate spatial models implemented 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).

Page views:: 1497. Submitted: 2019-07-31. Published: 2021-06-05.
Paper: Bayesian Multivariate Spatial Models for Lattice Data with INLA     Download PDF (Downloads: 518)
Supplements:
INLAMSM_0.2-3.tar.gz: R source package Download (Downloads: 36; 225KB)
v98i02.R: R replication code Download (Downloads: 57; 12KB)

DOI: 10.18637/jss.v098.i02

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Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.