glmmTMB: Generalized Linear Mixed Models using Template Model Builder

Fit linear and generalized linear mixed models with various extensions, including zero-inflation. The models are fitted using maximum likelihood estimation via 'TMB' (Template Model Builder). Random effects are assumed to be Gaussian on the scale of the linear predictor and are integrated out using the Laplace approximation. Gradients are calculated using automatic differentiation.

Version: 1.1.10
Depends: R (≥ 3.6.0)
Imports: methods, TMB (≥ 1.9.0), lme4 (≥ 1.1-18.9000), Matrix, nlme, numDeriv, mgcv, reformulas (≥ 0.2.0)
LinkingTo: TMB, RcppEigen
Suggests: knitr, rmarkdown, testthat, MASS, lattice, ggplot2 (≥ 2.2.1), mlmRev, bbmle (≥ 1.0.19), pscl, coda, reshape2, car (≥ 3.0.6), emmeans (≥ 1.4), estimability, DHARMa, multcomp, MuMIn, effects (≥ 4.0-1), dotwhisker, broom, broom.mixed, plyr, png, boot, texreg, xtable, huxtable, parallel, blme, purrr, dplyr, ade4, ape, gsl
Published: 2024-09-26
DOI: 10.32614/CRAN.package.glmmTMB
Author: Mollie Brooks ORCID iD [aut, cre], Ben Bolker ORCID iD [aut], Kasper Kristensen [aut], Martin Maechler ORCID iD [aut], Arni Magnusson ORCID iD [aut], Maeve McGillycuddy [ctb], Hans Skaug ORCID iD [aut], Anders Nielsen ORCID iD [aut], Casper Berg ORCID iD [aut], Koen van Bentham [aut], Nafis Sadat ORCID iD [ctb], Daniel Lüdecke ORCID iD [ctb], Russ Lenth [ctb], Joseph O'Brien ORCID iD [ctb], Charles J. Geyer [ctb], Mikael Jagan ORCID iD [ctb], Brenton Wiernik ORCID iD [ctb], Daniel B. Stouffer ORCID iD [ctb], Michael Agronah ORCID iD [ctb]
Maintainer: Mollie Brooks <mollieebrooks at gmail.com>
BugReports: https://github.com/glmmTMB/glmmTMB/issues
License: AGPL-3
URL: https://github.com/glmmTMB/glmmTMB
NeedsCompilation: yes
SystemRequirements: GNU make
Citation: glmmTMB citation info
Materials: NEWS
In views: Environmetrics, MixedModels
CRAN checks: glmmTMB results

Documentation:

Reference manual: glmmTMB.pdf
Vignettes: Covariance structures with glmmTMB (source, R code)
Hacking glmmTMB (source, R code)
Post-hoc MCMC with glmmTMB (source, R code)
Miscellaneous examples (source, R code)
Parallel optimization using glmmTMB (source, R code)
Priors in glmmTMB (source, R code)
Simulate from a fitted glmmTMB model or a formula (source, R code)
Troubleshooting with glmmTMB (source, R code)
basic examples of glmmTMB usage (source, R code)
Model evaluation (source, R code)

Downloads:

Package source: glmmTMB_1.1.10.tar.gz
Windows binaries: r-devel: glmmTMB_1.1.10.zip, r-release: glmmTMB_1.1.10.zip, r-oldrel: glmmTMB_1.1.10.zip
macOS binaries: r-devel (arm64): glmmTMB_1.1.10.tgz, r-release (arm64): glmmTMB_1.1.10.tgz, r-oldrel (arm64): glmmTMB_1.1.10.tgz, r-devel (x86_64): glmmTMB_1.1.10.tgz, r-release (x86_64): glmmTMB_1.1.10.tgz, r-oldrel (x86_64): glmmTMB_1.1.10.tgz
Old sources: glmmTMB archive

Reverse dependencies:

Reverse depends: gmvjoint, predictmeans
Reverse imports: cv, DEGRE, depower, GLMMcosinor, glmmSeq, iccCounts, lefko3, LongDat, Maaslin2, mecoturn, mtscr, multilevelmediation, muscat, pastaPlot, pdR, twosigma
Reverse suggests: afex, AICcmodavg, bayestestR, broom.helpers, broom.mixed, buildmer, DHARMa, easystats, ecostats, eyetrackingR, ggeffects, glmertree, gratia, insight, marginaleffects, metafor, mitml, mmrm, MOCHA, modelbased, multcomp, ordbetareg, parameters, performance, permutes, qra, RVAideMemoire, sdmTMB, see, sjPlot, tidybulk, tram, tramME, WeMix
Reverse enhances: MuMIn, texreg

Linking:

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