CARBayesST: Spatio-Temporal Generalised Linear Mixed Models for Areal Unit Data

Implements a class of spatio-temporal generalised linear mixed models for areal unit data, with inference in a Bayesian setting using Markov chain Monte Carlo (MCMC) simulation. The response variable can be binomial, Gaussian or Poisson, but for some models only the binomial and Poisson data likelihoods are available. The spatio-temporal autocorrelation is modelled by random effects, which are assigned conditional autoregressive (CAR) style prior distributions. A number of different random effects structures are available, and full details are given in the vignette accompanying this package and the references in the help files. The creation of this package was supported by the Engineering and Physical Sciences Research Council (EPSRC) grant EP/J017442/1 and the Medical Research Council (MRC) grant MR/L022184/1.

Version: 2.5
Depends: MASS, R (≥ 3.0.0), Rcpp (≥ 0.11.5)
Imports: CARBayesdata, coda, dplyr, matrixcalc, sp, spam, spdep, stats, testthat, truncdist, truncnorm, utils
LinkingTo: Rcpp
Published: 2017-03-16
Author: Duncan Lee, Alastair Rushworth and Gary Napier
Maintainer: Duncan Lee <Duncan.Lee at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
In views: SpatioTemporal
CRAN checks: CARBayesST results


Reference manual: CARBayesST.pdf
Vignettes: Vignette for \textbf{CARBayesST} package.
Package source: CARBayesST_2.5.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X Mavericks binaries: r-release: CARBayesST_2.5.tgz, r-oldrel: CARBayesST_2.5.tgz
Old sources: CARBayesST archive


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