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).
| Version: | 0.1.1 |
| Depends: | R (≥ 3.5) |
| Imports: | Rcpp, stats, Formula, tibble, dplyr, ggplot2 |
| LinkingTo: | Rcpp |
| Published: | 2025-12-22 |
| DOI: | 10.32614/CRAN.package.MBRM |
| Author: | Lizandra C. Fabio [aut], Vanessa Barros [aut], Cristian Lobos [aut], Jalmar M. F. Carrasco [aut, cre] |
| Maintainer: | Jalmar M. F. Carrasco <carrasco.jalmar at ufba.br> |
| License: | GPL-3 |
| NeedsCompilation: | yes |
| CRAN checks: | MBRM results |
| Reference manual: | MBRM.html , MBRM.pdf |
| Package source: | MBRM_0.1.1.tar.gz |
| Windows binaries: | r-devel: MBRM_0.1.1.zip, r-release: MBRM_0.1.1.zip, r-oldrel: MBRM_0.1.1.zip |
| macOS binaries: | r-release (arm64): MBRM_0.1.1.tgz, r-oldrel (arm64): MBRM_0.1.1.tgz, r-release (x86_64): MBRM_0.1.1.tgz, r-oldrel (x86_64): MBRM_0.1.1.tgz |
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