CARBayesST
4.0Spatio-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
- NOTE r-devel-linux-x86_64-debian-clang
- NOTE r-devel-linux-x86_64-debian-gcc
- NOTE2026-06-0911 OK · 2 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- ERROR2026-06-0811 OK · 1 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
- NOTE2026-04-2210 OK · 4 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- ERROR2026-04-189 OK · 4 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
- NOTE2026-03-1010 OK · 4 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
- Examples that run
- 100%
- Documented parameters
- 100%
- Return-value docs
- 100%
- References docs
- 63%
Downloads
Repository
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Dependencies
Code & Tests
- Cyclomatic complexity
- 1.0 median / 111 max
Test coverage
Line coverage
–
Expression
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Tests / Examples
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Functions
339 9 exported
Complexity
16.3 avg / 111 max
Call network
339 nodes / 672 edges
Call graph
Open call graph →Lowest coverage
Per-function coverage is not measured for this package yet.
People & History
Author records are not tracked yet for this package.
22 releases. Pick two to compare their code metrics. R releases are shown for context.
- 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
- 3.22021-03-31 · diff ↗
- 3.1.12021-02-04 · diff ↗
- RR 4.0.0 released · 2020-04-24
- 3.12020-03-09 · diff ↗
Show 19 earlier events
- 3.0.22019-12-12 · diff ↗
- RR 3.6.0 released · 2019-04-26
- 3.0.12019-01-08 · diff ↗
- 3.02018-09-27 · diff ↗
- 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 ↗
- 2.12015-08-26 · diff ↗
- 2.02015-07-06 · diff ↗
- RR 3.2.0 released · 2015-04-16
- 1.12014-11-14 · diff ↗
- 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
- Installed size
- not tracked yet
- With dependencies
- not tracked yet