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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>.
Getting started
Browse package contents
Package details |
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| Author | Matt P. Wand [aut, cre], James C.F. Yu [aut] |
| Maintainer | Matt P. Wand <matt.wand@uts.edu.au> |
| License | GPL (>= 2) |
| Version | 1.0-3.1 |
| Package repository | View on CRAN |
| Installation |
Install the latest version of this package by entering the following in R:
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