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glmmrBase: Monte Carlo Maximum Likelihood and Analysis of Generalised Linear Mixed Models

Specification, analysis, simulation, and fitting of generalised linear mixed models. Monte Carlo Maximum likelihood model fitting for a range of models, non-linear fixed effect specifications, a wide range of flexible covariance functions including Gaussian Process approximations. Methods described in Watson, Wang, and Giorgi (2026) <doi:10.48550/arXiv.2601.16022>.

Version: 1.4.1
Depends: R (≥ 3.5.0), Matrix (≥ 1.3-1)
Imports: methods, Rcpp (≥ 1.0.11), R6
LinkingTo: Rcpp (≥ 1.0.11), RcppEigen, BH, RcppParallel (≥ 5.0.1)
Suggests: fmesher, lme4
Published: 2026-05-28
DOI: 10.32614/CRAN.package.glmmrBase
Author: Sam Watson [aut, cre]
Maintainer: Sam Watson <S.I.Watson at bham.ac.uk>
BugReports: https://github.com/samuel-watson/glmmrBase/issues
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://github.com/samuel-watson/glmmrBase
NeedsCompilation: yes
SystemRequirements: GNU make
In views: MixedModels
CRAN checks: glmmrBase results

Documentation:

Reference manual: glmmrBase.html , glmmrBase.pdf

Downloads:

Package source: glmmrBase_1.4.1.tar.gz
Windows binaries: r-devel: glmmrBase_1.4.1.zip, r-release: not available, r-oldrel: not available
macOS binaries: r-release (arm64): glmmrBase_1.4.1.tgz, r-oldrel (arm64): glmmrBase_1.4.1.tgz, r-release (x86_64): glmmrBase_1.4.1.tgz, r-oldrel (x86_64): glmmrBase_1.4.1.tgz
Old sources: glmmrBase archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=glmmrBase to link to this page.

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.