Spatio-Temporal Generalised Linear Mixed Models for Areal Unit Data
Overview
Implements a class of univariate and multivariate 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, including models similar to Rushworth et al. (2014) doi:10.1016/j.sste.2014.05.001. Full details are given in the vignette accompanying this package. The creation and development of this package was supported by the Engineering and Physical Sciences Research Council (EPSRC) grants EP/J017442/1 and EP/T004878/1 and the Medical Research Council (MRC) grant MR/L022184/1.
Install
Health
NOTECRAN incoming feasibilityr-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc
Maintainer: ‘Duncan Lee <Duncan.Lee@glasgow.ac.uk>’
No Authors@R field in DESCRIPTION.
Please add one, modifying
Authors@R: c(person(given = "Duncan",
family = "Lee",
role = c("aut", "cre"),
email = "duncan.lee@glasgow.ac.uk"),
person(given = "Alastair",
family = "Rushworth",
role = "aut"),
person(given = "Gary",
family = "Napier",
role = "aut"),
person(given = "William",
family = "Pettersson",
role = "aut"))
as necessary.- NOTE11 OK, 2 NOTE2026-06-09
- ERROR11 OK, 1 NOTE, 1 ERROR2026-06-08
- NOTE10 OK, 4 NOTE2026-04-22
- ERROR9 OK, 4 NOTE, 1 ERROR2026-04-18
- NOTE10 OK, 4 NOTE2026-03-10
Documentation
- Help pages
- 16includes a package overview page
- Examples that run
- 90%9 run in a plain check · 1 hold no code
- Exported functions with examples
- 100%
- Documented parameters
- 100%
- Return-value docs
- 100%
- Help pages citing references
- 63%
Downloads
Repository
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1 development-tooling and community-health practice detected across 1 family in the upstream repository
Checks run against github.com/duncanplee/carbayesst on 2026-10-11.
Dependencies
Installing CARBayesST adds 94 packages (52 with compiled code, 94 MB of source tarballs). Heaviest: stringi 11 MB, sf 9.3 MB, ggplot2 6.0 MB.
Code & Tests
People & History
Maintainer since 1.0 (2014)
Pick two releases to compare their code metrics.
- RR 4.6.0 released · 2026-04-24
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- 4.0Latest
- RR 4.3.0 released · 2023-04-21
- 3.3.12023-01-17 · diff ↗
- 3.32022-05-12 · diff ↗
- 3.2.32022-04-26 · diff ↗
- RR 4.2.0 released · 2022-04-22
- 3.2.22022-03-16 · diff ↗
- 3.2.12021-05-31 · diff ↗
- RR 4.1.0 released · 2021-05-18
- 3.2
- 3.1.12021-02-04 · diff ↗
- RR 4.0.0 released · 2020-04-24
- 3.12020-03-09 · diff ↗
Show 19 earlier eventsHide 19 earlier events
- 3.0.22019-12-12 · diff ↗
- RR 3.6.0 released · 2019-04-26
- 3.0.12019-01-08 · diff ↗
- 3.0
- RR 3.5.0 released · 2018-04-23
- 2.5.22018-04-17 · diff ↗
- 2.5.12017-08-14 · diff ↗
- RR 3.4.0 released · 2017-04-21
- 2.52017-03-16 · diff ↗
- 2.42016-07-28 · diff ↗
- 2.32016-06-15 · diff ↗
- RR 3.3.0 released · 2016-05-03
- 2.22016-02-25 · diff ↗
- 2.1
- 2.02015-07-06 · diff ↗ ·
removed 8 exports
ST.KHmain, ST.KHinteraction, ST.cluster, ST.ARCAR, ST.ARCARcluster, ST.ARCARadaptive, results.summarise, print.carbayesSTadded 5 exports
ST.CARlinear, ST.CARar, ST.CARanova, ST.CARadaptive, ST.CARlocalised - RR 3.2.0 released · 2015-04-16
- 1.12014-11-14 · diff ↗ ·
removed 5 exports
ST.knorrheld.int, ST.knorrheld.main, ST.clustconv, ST.clustonly, ST.clustcaradded 6 exports
ST.KHmain, ST.KHinteraction, ST.cluster, ST.ARCAR, ST.ARCARcluster, ST.ARCARadaptive - 1.02014-08-11
- RR 3.1.0 released · 2014-04-10
Package metadata
- First published
- 2014-08-11
- Total releases
- 22 / 12 yrs
- License
- GPL (>= 2) OSI
- Minimum R
- ≥ 3.5.0
- Download size
- 3.2 MB
Cite
Cite this package
Run in R for the authors' entry:
citation("CARBayesST")The package provides a citation file, so citation() returns the authors' own entry.
It points to 10.18637/jss.v084.i09.
Cite the R Observatory
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From data release v2026-10-18, which the citation names so these numbers can be found later. More on citing and the projects behind them.