This Article Full Text (PDF) References Alert me when this article is cited Alert me if a correction is posted Services Email this article to a friend Similar articles in this journal Alert me to new issues of the journal Add to Saved Citations Download to citation manager Add to My Marked Citations Citing Articles Citing Articles via Scopus Google Scholar Articles by Cazzaro, M. Articles by Colombi, R. Social Bookmarking                         What's this?

Multinomial-Poisson models subject to inequality constraints

Dipartimento di Metodi Quantitativi per le Scienze Economiche ed Aziendali, Università di Milano-Bicocca, Italy

Roberto Colombi

Dipartimento di Ingegneria dell’Informazione e Metodi Matematici, Università di Bergamo, Italy. E-mail: colombi{at}unibg.it

Lang’s Multinomial-Poisson Homogeneous (MPH) models and Homogeneous Linear Predictor (HLP) Multinomial-Poisson models include as special cases many models for contingency table analysis that have been introduced in the effort to overcome well-known limitations of the log-linear models. Here the definitions of MPH and HLP models are extended to include inequality constraints. It is shown that inequality constrained MPH and HLP models are very flexible and rich family of models for contingency table analysis. The inequality constrained hierarchical multinomial marginal models which are an important sub-class of MPH models are also examined.

Key Words: constrained statistical inference • generalized odds ratios • marginal models • multinomial-Poisson homogeneous models • multivariate logit models

Statistical Modelling, Vol. 9, No. 3, 215-233 (2009)
DOI: 10.1177/1471082X0800900303


CiteULike    Complore    Connotea    Del.icio.us    Digg    Reddit    Technorati    Twitter    What's this?