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- Publisher
- Oxford University Press
- Copyright
- 2013 Biometrika Trust
- Subject
- Articles
- ISSN
- 0006-3444
- eISSN
- 1464-3510
- DOI
- 10.1093/biomet/ass080
- Publisher site
- See Article on Publisher Site
Abstract
This paper introduces a novel class of models for binary data, which we call log-mean linear models. They are specified by linear constraints on the log-mean linear parameter, defined as a log-linear expansion of the mean parameter of the multivariate Bernoulli distribution. We show that marginal independence relationships between variables can be specified by setting certain log-mean linear interactions to zero and, more specifically, that graphical models of marginal independence are log-mean linear models. Our approach overcomes some drawbacks of the existing parameterizations of graphical models of marginal independence.
Journal
Biometrika – Oxford University Press
Published: Jun 5, 2013
Keywords: Contingency table Graphical Markov model Marginal independence Mean parameter