The VGAM Package for Categorical Data Analysis

Show simple item record Yee, Thomas en 2012-03-18T23:05:04Z en 2010-01 en
dc.identifier.citation Journal of Statistical Software 32(10):1-34 2010 en
dc.identifier.issn 1548-7660 en
dc.identifier.uri en
dc.description.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. en
dc.description.uri en
dc.language EN en
dc.publisher American Statistical Association en
dc.relation.ispartofseries Journal of Statistical Software en
dc.rights Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated. Previously published items are made available in accordance with the copyright policy of the publisher. en
dc.rights.uri en
dc.subject categorical data analysis en
dc.subject Fisher scoring en
dc.subject iteratively reweighted least squares en
dc.subject multinomial distribution en
dc.subject nominal and ordinal polytomous responses en
dc.subject smoothing en
dc.subject vector generalized linear and additive models en
dc.subject VGAM R package en
dc.subject ADDITIVE-MODELS en
dc.subject REGRESSION en
dc.title The VGAM Package for Categorical Data Analysis en
dc.type Journal Article en
pubs.issue 10 en
pubs.begin-page 1 en
pubs.volume 32 en
dc.rights.holder Copyright: American Statistical Association en en
pubs.end-page 34 en
pubs.publication-status Published en
dc.rights.accessrights en
pubs.subtype Article en
pubs.elements-id 89284 en Science en Statistics en
pubs.record-created-at-source-date 2010-09-01 en

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