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>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.0-3.1 |
rolling linux/jammy R-4.5 | glmmEP_1.0-3.1.tar.gz |
223.9 KiB |
1.0-3.1 |
rolling linux/noble R-4.5 | glmmEP_1.0-3.1.tar.gz |
223.3 KiB |
1.0-3.1 |
rolling source/ R- | glmmEP_1.0-3.1.tar.gz |
391.0 KiB |
1.0-3.1 |
latest linux/jammy R-4.5 | glmmEP_1.0-3.1.tar.gz |
223.9 KiB |
1.0-3.1 |
latest linux/noble R-4.5 | glmmEP_1.0-3.1.tar.gz |
223.3 KiB |
1.0-3.1 |
latest source/ R- | glmmEP_1.0-3.1.tar.gz |
391.0 KiB |
1.0-3.1 |
2026-04-26 source/ R- | glmmEP_1.0-3.1.tar.gz |
391.0 KiB |
1.0-3.1 |
2026-04-23 source/ R- | glmmEP_1.0-3.1.tar.gz |
391.0 KiB |
1.0-3.1 |
2026-04-09 windows/windows R-4.5 | glmmEP_1.0-3.1.zip |
231.5 KiB |
1.0-3.1 |
2025-04-20 source/ R- | glmmEP_1.0-3.1.tar.gz |
391.0 KiB |