glmmEP: Generalized Linear Mixed Model Analysis via Expectation Propagation

Approximate frequentist inference for generalized linear mixed model analysis with expectation propagation used to circumvent the need for multivariate integration. In this version, the random effects can be any reasonable dimension. However, only probit mixed models with one level of nesting are supported. The methodology is described in Hall, Johnstone, Ormerod, Wand and Yu (2018) <arXiv:1805.08423v1>.

Version:	1.0-3.1
Depends:	stats
Imports:	lme4, matrixcalc
Suggests:	mlmRev
Published:	2019-10-15
Author:	Matt P. Wand [aut, cre], James C.F. Yu [aut]
Maintainer:	Matt P. Wand <matt.wand at uts.edu.au>
License:	GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation:	yes
CRAN checks:	glmmEP results

Documentation:

Reference manual:	glmmEP.pdf
Vignettes:	glmmEP User Manual

Downloads:

Package source:	glmmEP_1.0-3.1.tar.gz
Windows binaries:	r-devel: glmmEP_1.0-3.1.zip, r-release: glmmEP_1.0-3.1.zip, r-oldrel: glmmEP_1.0-3.1.zip
macOS binaries:	r-release (arm64): glmmEP_1.0-3.1.tgz, r-oldrel (arm64): glmmEP_1.0-3.1.tgz, r-release (x86_64): glmmEP_1.0-3.1.tgz, r-oldrel (x86_64): glmmEP_1.0-3.1.tgz
Old sources:	glmmEP archive

Linking:

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