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The mode oriented stochastic search (MOSS) algorithm for log-linear models with conjugate priors

Authors
Journal
Statistical Methodology
1572-3127
Publisher
Elsevier
Publication Date
Volume
7
Issue
3
Identifiers
DOI: 10.1016/j.stamet.2009.04.002
Keywords
  • Bayesian Analysis
  • Contingency Table
  • Hierarchical Log-Linear Model
  • Markov Chain Monte Carlo
  • Model Selection
  • Stochastic Search
Disciplines
  • Computer Science
  • Mathematics

Abstract

Abstract We describe a novel stochastic search algorithm for rapidly identifying regions of high posterior probability in the space of decomposable, graphical and hierarchical log-linear models. Our approach is based on the Diaconis–Ylvisaker conjugate prior for log-linear parameters. We discuss the computation of Bayes factors through Laplace approximations and the Bayesian iterative proportional fitting algorithm for sampling model parameters. We use our model determination approach in a sparse eight-way contingency table.

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