Published by the Foundation for Open Access Statistics Editors-in-chief: Bettina Grün, Torsten Hothorn, Rebecca Killick, Edzer Pebesma, Achim Zeileis    ISSN 1548-7660; CODEN JSSOBK
Authors: Thomas W. Yee
Title: The VGAM Package for Categorical Data Analysis
Abstract: Classical categorical regression models such as the multinomial logit and proportional odds models are shown to be readily handled by the vector generalized linear and additive model (VGLM/VGAM) framework. Additionally, there are natural extensions, such as reduced-rank VGLMs for dimension reduction, and allowing covariates that have values specific to each linear/additive predictor, e.g., for consumer choice modeling. This article describes some of the framework behind the VGAM R package, its usage and implementation details.

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Paper: The VGAM Package for Categorical Data Analysis     Download PDF (Downloads: 20202)
Supplements:
VGAM_0.7-10.tar.gz: R source package Download (Downloads: 1530; 1MB)
v32i10.R: R example code from the paper Download (Downloads: 1771; 11KB)
DOI: 10.18637/jss.v032.i10

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Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.