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>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
In views: MixedModels
CRAN checks: glmmEP results


Reference manual: glmmEP.pdf
Vignettes: glmmEP User Manual


Package source: glmmEP_1.0-3.1.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
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


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