glmm: Generalized Linear Mixed Models via Monte Carlo Likelihood Approximation

Approximates the likelihood of a generalized linear mixed model using Monte Carlo likelihood approximation. Then maximizes the likelihood approximation to return maximum likelihood estimates, observed Fisher information, and other model information.

Version: 1.4.4
Depends: R (≥ 4.0), trust, mvtnorm, Matrix, parallel, doParallel
Imports: stats, foreach, itertools, utils
Suggests: knitr
Published: 2022-10-09
DOI: 10.32614/CRAN.package.glmm
Author: Christina Knudson [aut, cre], Charles J. Geyer [ctb], Sydney Benson [ctb]
Maintainer: Christina Knudson <drchristinaknudson at>
License: GPL-2
NeedsCompilation: yes
In views: MixedModels
CRAN checks: glmm results


Reference manual: glmm.pdf
Vignettes: author2019mypaper


Package source: glmm_1.4.4.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): glmm_1.4.4.tgz, r-oldrel (arm64): glmm_1.4.4.tgz, r-release (x86_64): glmm_1.4.4.tgz, r-oldrel (x86_64): glmm_1.4.4.tgz
Old sources: glmm archive


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