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Parameterizations and fitting of bi-directed graph models to categorical data

Lupparelli, Monia, Marchetti, Giovanni M. and Bergsma, Wicher (2009) Parameterizations and fitting of bi-directed graph models to categorical data. Scandinavian journal of statistics, 36 (3). pp. 559-576. ISSN 0303-6898

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Abstract

We discuss two parameterizations of models for marginal independencies for discrete distributions which are representable by bi-directed graph models, under the global Markov property. Such models are useful data analytic tools especially if used in combination with other graphical models. The first parameterization, in the saturated case, is also known as thenation multivariate logistic transformation, the second is a variant that allows, in some (but not all) cases, variation-independent parameters. An algorithm for maximum likelihood fitting is proposed, based on an extension of the Aitchison and Silvey method.

Item Type: Article
Official URL: http://onlinelibrary.wiley.com/journal/10.1111/(IS...
Additional Information: © 2009 oard of the Foundation of the Scandinavian Journal of Statistics
Uncontrolled Keywords: complete hierarchical parameterizations, connected set Markov property, constrained maximum likelihood, covariance graphs, marginal independence, marginal log-linear models, multivariate logistic transformation, variation independence
Library of Congress subject classification: H Social Sciences > HA Statistics
Sets: Departments > Statistics
Rights: http://www.lse.ac.uk/library/rights/LSERO.htm
URL: http://eprints.lse.ac.uk/30453/

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