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).

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

Documentation:

Reference manual:

MBRM.html , MBRM.pdf

Downloads:

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

Linking:

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