glmmrBase: Generalised Linear Mixed Models in R

Specification, analysis, simulation, and fitting of generalised linear mixed models. Includes Markov Chain Monte Carlo Maximum likelihood and Laplace approximation model fitting for a range of models, non-linear fixed effect specifications, a wide range of flexible covariance functions that can be combined arbitrarily, robust and bias-corrected standard error estimation, power calculation, data simulation, and more. See <> for a detailed manual.

Version: 0.9.2
Depends: R (≥ 3.5.0), Matrix (≥ 1.3-1)
Imports: methods, Rcpp (≥ 1.0.11), R6, rstan (≥ 2.32.1), rstantools (≥
LinkingTo: Rcpp (≥ 1.0.11), RcppEigen, SparseChol (≥ 0.3.1), BH, RcppParallel (≥ 5.0.1), rstan (≥ 2.32.1), StanHeaders (≥ 2.32.0)
Published: 2024-06-19
DOI: 10.32614/CRAN.package.glmmrBase
Author: Sam Watson [aut, cre]
Maintainer: Sam Watson <S.I.Watson at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
SystemRequirements: GNU make
In views: MixedModels
CRAN checks: glmmrBase results


Reference manual: glmmrBase.pdf


Package source: glmmrBase_0.9.2.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): glmmrBase_0.9.2.tgz, r-oldrel (arm64): glmmrBase_0.9.2.tgz, r-release (x86_64): glmmrBase_0.9.2.tgz, r-oldrel (x86_64): glmmrBase_0.9.2.tgz
Old sources: glmmrBase archive

Reverse dependencies:

Reverse depends: glmmrOptim
Reverse linking to: glmmrOptim, rts2


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