Chain graph models of multivariate regression type for categorical data

2009/06/30 by Giovanni M. Marchetti, Monia Lupparelli · 1 citation
Mathematics · #stat.ME #math.ST #stat.TH

paper · pdf · doi:10.3150/10-bej300

published as Bernoulli 2011, Vol. 17, No. 3, 827-844 · Published in at http://dx.doi.org/10.3150/10-BEJ300 the Bernoulli (http://isi.cbs.nl/bernoulli/) by the International Statistical Institute/Bernoulli Society (http://isi.cbs.nl/BS/bshome.htm)

arxiv created 2011/07/13 · arxiv updated 2011/07/14

Abstract

We discuss a class of chain graph models for categorical variables defined by what we call a multivariate regression chain graph Markov property. First, the set of local independencies of these models is shown to be Markov equivalent to those of a chain graph model recently defined in the literature. Next we provide a parametrization based on a sequence of generalized linear models with a multivariate logistic link function that captures all independence constraints in any chain graph model of this kind.

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• On the Properties of MVR Chain Graphs

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