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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) <doi:10.48550/arXiv.1805.08423>.
| 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 |
| 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: 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 |
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