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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 cdf function for the linkage, and Z, the design matrix.
Getting started
README.md
An example of variable selection in `GLMcat`
A Tutorial on fitting Generalized Linear Models with the GLMcat Package
Discrete Choice Models in GLMcat
An example of discrete choice modeling in `GLMcat`
An example of variable selection in `GLMcat`"
A tutorial on fitting Generalized Linear Models for categorical responses with the GLMcat package"
Browse package contents
Package details |
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| Author | Lorena León [aut, cre], Jean Peyhardi [aut], Catherine Trottier [aut] |
| Maintainer | Lorena León <ylorenaleonv@gmail.com> |
| License | GPL-3 |
| Version | 0.2.7 |
| URL | https://github.com/ylleonv/GLMcat |
| Package repository | View on CRAN |
| Installation |
Install the latest version of this package by entering the following in R:
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Try the GLMcat package in your browser
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