The admissibility of the maximum likelihood estimator for decomposable log-linear interaction models for contingency tables

Glen Meeden, Joseph Lang, Charles Geyer, Eiichiro Funo

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

It is well known that for certain log-linear interaction models for contingency tables, i.e. those that are decomposable, the maximum likelihood estimator can be found explicitly. In this note we will show that in such cases this estimator is admissible. The proof is based on a stepwise Bayes argument and is a generalization of a proof of the admissibility of the maximum likelihood estimator for the usual unconstrained multinomial model. It is then shown that this result is a special case of a result for discrete exponential families.

Original languageEnglish (US)
Pages (from-to)473-493
Number of pages21
JournalCommunications in Statistics - Theory and Methods
Volume27
Issue number2
DOIs
StatePublished - Jan 1 1998

Keywords

  • Exponential families
  • Graphical models
  • Stepwise bayes

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