MBRM
Mixed Regression Models with Generalized Log-Gamma Random Effects
Multivariate distribution derived from a Bernoulli mixed model under a marginal approach, incorporating a non-normal random intercept whose distribution is assumed to follow a generalized log-gamma (GLG) specification under a particular parameter setting. Estimation is performed by maximizing the log-likelihood using numerical optimization techniques (Lizandra C. Fabio, Vanessa Barros, Cristian Lobos, Jalmar M. F. Carrasco, Marginal multivariate approach: A novel strategy for handling correlated binary outcomes, 2025, under submission).
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.1.1 |
rolling linux/jammy R-4.5 | MBRM_0.1.1.tar.gz |
90.7 KiB |
0.1.1 |
rolling linux/noble R-4.5 | MBRM_0.1.1.tar.gz |
92.0 KiB |
0.1.1 |
rolling source/ R- | MBRM_0.1.1.tar.gz |
17.4 KiB |
0.1.1 |
latest linux/jammy R-4.5 | MBRM_0.1.1.tar.gz |
90.7 KiB |
0.1.1 |
latest linux/noble R-4.5 | MBRM_0.1.1.tar.gz |
92.0 KiB |
0.1.1 |
latest source/ R- | MBRM_0.1.1.tar.gz |
17.4 KiB |
0.1.1 |
2026-04-26 source/ R- | MBRM_0.1.1.tar.gz |
17.4 KiB |
0.1.1 |
2026-04-23 source/ R- | MBRM_0.1.1.tar.gz |
17.4 KiB |
0.1.1 |
2026-04-09 windows/windows R-4.5 | MBRM_0.1.1.zip |
414.8 KiB |