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ref.ICAR: Objective Bayes Intrinsic Conditional Autoregressive Model forAreal Data

Implements an objective Bayes intrinsic conditional autoregressive prior. This model provides an objective Bayesian approach for modeling spatially correlated areal data using an intrinsic conditional autoregressive prior on a vector of spatial random effects.

Version:2.0.2
Imports:sf,sp,spdep,mvtnorm,coda,MCMCglmm,Rdpack, graphics,pracma, stats,classInt,dplyr,ggplot2,gtools
Suggests:maps,MASS,knitr,rmarkdown,RColorBrewer,rcrossref,spData,formatR
Published:2025-01-22
DOI:10.32614/CRAN.package.ref.ICAR
Author:Erica M. Porter [aut, cre], Matthew J. Keefe [aut], Christopher T. Franck [aut], Marco A.R. Ferreira [aut]
Maintainer:Erica M. Porter <emporte at clemson.edu>
License:MIT + fileLICENSE
NeedsCompilation:no
Materials:README
CRAN checks:ref.ICAR results

Documentation:

Reference manual:ref.ICAR.html ,ref.ICAR.pdf
Vignettes:Applying an ICAR reference prior (source,R code)

Downloads:

Package source: ref.ICAR_2.0.2.tar.gz
Windows binaries: r-devel:ref.ICAR_2.0.2.zip, r-release:ref.ICAR_2.0.2.zip, r-oldrel:ref.ICAR_2.0.2.zip
macOS binaries: r-release (arm64):ref.ICAR_2.0.2.tgz, r-oldrel (arm64):ref.ICAR_2.0.2.tgz, r-release (x86_64):ref.ICAR_2.0.2.tgz, r-oldrel (x86_64):ref.ICAR_2.0.2.tgz
Old sources: ref.ICAR archive

Linking:

Please use the canonical formhttps://CRAN.R-project.org/package=ref.ICARto link to this page.


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