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 (Journal of the American Statistical Association, 2020).


Reference manual

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install.packages("glmmEP")

1.0-4 by Matt P. Wand, a month ago


Browse source code at https://github.com/cran/glmmEP


Authors: Matt P. Wand [aut, cre] , James C.F. Yu [aut] , Cleve Moler [ctb] (LINPACK routines in src)


Documentation:   PDF Manual  


GPL (>= 2) license


Imports lme4, matrixcalc

Depends on stats

Suggests mlmRev


See at CRAN