Cookies?
Library Header Image
LSE Research Online LSE Library Services

Marginal log-linear parameterization of conditional independence models

Rudas, Tamas, Bergsma, Wicher and Nemeth, Renáta (2010) Marginal log-linear parameterization of conditional independence models. Biometrika, 97 (4). pp. 1006-1012. ISSN 0006-3444

Full text not available from this repository.

Abstract

Models defined by a set of conditional independence restrictions play an important role in statistical theory and applications, especially, but not only, in graphical modelling. In this paper we identify a subclass of these consisting of hierarchical marginal log-linear models, as defined by Bergsma & Rudas (2002a). Such models are smooth, which implies the applicability of standard asymptotic theory and simplifies interpretation. Furthermore, we give a marginal log-linear parameterization and a minimal specification of the models in the subclass, which implies the applicability of standard methods to compute maximum likelihood estimates and simplifies the calculation of the degrees of freedom of chi-squared statistics to test goodness-of-fit. The utility of the results is illustrated by applying them to block-recursive Markov models associated with chain graphs.

Item Type: Article
Official URL: http://www.oxfordjournals.org/our_journals/biomet/...
Additional Information: © 2010 Biometrika Trust
Library of Congress subject classification: Q Science > QA Mathematics
Sets: Departments > Statistics
Rights: http://www.lse.ac.uk/library/usingTheLibrary/academicSupport/OA/depositYourResearch.aspx
Date Deposited: 11 Feb 2011 15:09
URL: http://eprints.lse.ac.uk/32504/

Actions (login required)

Record administration - authorised staff only Record administration - authorised staff only