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:	1.4.3
Depends:	R (≥ 4.0), trust, mvtnorm, Matrix, parallel, doParallel
Imports:	stats, foreach, itertools, utils
Suggests:	knitr
Published:	2022-04-07
Author:	Christina Knudson [aut, cre], Charles J. Geyer [ctb], Sydney Benson [ctb]
Maintainer:	Christina Knudson <knud8583 at stthomas.edu>
License:	GPL-2
NeedsCompilation:	yes
CRAN checks:	glmm results

Documentation:

Reference manual:	glmm.pdf
Vignettes:	author2019mypaper

Downloads:

Package source:	glmm_1.4.3.tar.gz
Windows binaries:	r-devel: glmm_1.4.3.zip, r-release: glmm_1.4.3.zip, r-oldrel: glmm_1.4.3.zip
macOS binaries:	r-release (arm64): glmm_1.4.3.tgz, r-oldrel (arm64): glmm_1.4.3.tgz, r-release (x86_64): glmm_1.4.3.tgz, r-oldrel (x86_64): glmm_1.4.3.tgz
Old sources:	glmm archive

Linking:

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