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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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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.