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MCMCglmm: MCMC Generalised Linear Mixed Models

Fits Multivariate Generalised Linear Mixed Models (and related models) using Markov chain Monte Carlo techniques (Hadfield 2010 J. Stat. Soft.).

Version: 2.35
Depends: Matrix, coda, ape
Imports: corpcor, tensorA, cubature, methods
Suggests: rgl, combinat, mvtnorm, orthopolynom, MCMCpack, bayesm, msm
Published: 2023-06-30
Author: Jarrod Hadfield
Maintainer: Jarrod Hadfield <j.hadfield at ed.ac.uk>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
Citation: MCMCglmm citation info
In views: Bayesian, MixedModels, Phylogenetics, Psychometrics, Survival
CRAN checks: MCMCglmm results

Documentation:

Reference manual: MCMCglmm.pdf

Downloads:

Package source: MCMCglmm_2.35.tar.gz
Windows binaries: r-devel: MCMCglmm_2.35.zip, r-release: MCMCglmm_2.35.zip, r-oldrel: MCMCglmm_2.35.zip
macOS binaries: r-release (arm64): MCMCglmm_2.35.tgz, r-oldrel (arm64): MCMCglmm_2.35.tgz, r-release (x86_64): MCMCglmm_2.35.tgz, r-oldrel (x86_64): MCMCglmm_2.35.tgz
Old sources: MCMCglmm archive

Reverse dependencies:

Reverse depends: MCMC.OTU, MCMC.qpcr
Reverse imports: BayesMultiMode, BiostatsUHNplus, mfa, NO.PING.PONG, ref.ICAR, StempCens
Reverse suggests: agridat, brms, broom.mixed, dispRity, ecostats, gap, ggeffects, insight, marginaleffects, miceadds, parameters, phyr, rotl, tidybayes
Reverse enhances: emmeans, MuMIn

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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