GLMcat: Generalized Linear Models for Categorical Responses

In statistical modeling, there is a wide variety of regression models for categorical dependent variables (nominal or ordinal data); yet, there is no software embracing all these models together in a uniform and generalized format. Following the methodology proposed by Peyhardi, Trottier, and Guédon (2015) <doi:10.1093/biomet/asv042>, we introduce 'GLMcat', an R package to estimate generalized linear models implemented under the unified specification (r, F, Z). Where r represents the ratio of probabilities (reference, cumulative, adjacent, or sequential), F the cumulative distribution function for the linkage, and Z, the design matrix.

Version: 0.1.0
Depends: R (≥ 2.10)
Imports: Rcpp, stats, base
LinkingTo: Rcpp, BH, RcppEigen
Suggests: knitr, rmarkdown, testthat, dplyr, ggplot2, gridExtra, gtools, tidyr
Published: 2020-12-18
Author: Lorena Leon [aut, cre], Jean Peyhardi [aut], Catherine Trottier [aut]
Maintainer: Lorena Leon <ylorenaleonv at>
License: GPL-3
NeedsCompilation: yes
Materials: README
CRAN checks: GLMcat results


Reference manual: GLMcat.pdf
Vignettes: Discrete Choice Models in GLMcat
A Tutorial on fitting Generalized Linear Models with the GLMcat Package
Package source: GLMcat_0.1.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release: GLMcat_0.1.0.tgz, r-oldrel: GLMcat_0.1.0.tgz


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