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A new specification of generalized linear models for categorical data

Jean Peyhardi 1, 2 Catherine Trottier 2 Yann Guédon 1, 3 
1 VIRTUAL PLANTS - Modeling plant morphogenesis at different scales, from genes to phenotype
CRISAM - Inria Sophia Antipolis - Méditerranée , INRA - Institut National de la Recherche Agronomique, UMR AGAP - Amélioration génétique et adaptation des plantes méditerranéennes et tropicales
Abstract : Regression models for categorical data are specified in heterogeneous ways. We propose to unify the specification of such models. This allows us to define the family of reference models for nominal data. We introduce the notion of reversible models for ordinal data that distinguishes adjacent and cumulative models from sequential ones. The combination of the proposed specification with the definition of reference and reversible models and various invariance properties leads to a new view of regression models for categorical data.
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Preprints, Working Papers, ...
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Contributor : Jean Peyhardi Connect in order to contact the contributor
Submitted on : Wednesday, April 30, 2014 - 10:14:43 AM
Last modification on : Friday, August 5, 2022 - 10:34:03 AM

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  • HAL Id : hal-00985595, version 1
  • ARXIV : 1404.7331


Jean Peyhardi, Catherine Trottier, Yann Guédon. A new specification of generalized linear models for categorical data. 2014. ⟨hal-00985595⟩



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