CARBayesST: Spatio-Temporal Generalised Linear Mixed Models for Areal Unit Data
Version 2.5

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.

Package details

AuthorDuncan Lee, Alastair Rushworth and Gary Napier
Date of publication2017-03-16 12:26:02
MaintainerDuncan Lee <>
LicenseGPL (>= 2)
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:

Try the CARBayesST package in your browser

Any scripts or data that you put into this service are public.

CARBayesST documentation built on May 29, 2017, 8:47 p.m.