MONIA LUPPARELLI GIOVANNI M. MARCHETTI WICHER P. BERGSMA
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. Copyright (c) 2009 Board of the Foundation of the Scandinavian Journal of Statistics.
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Article provided by Danish Society for Theoretical Statistics, Finnish Statistical Society, Norwegian Statistical Association and Swedish Statistical Association in its journal Scandinavian Journal of Statistics.