Bayesian analysis for reversible Markov chains

P. Diaconis, S.W.W. Rolles

Research output: Contribution to journalArticleAcademicpeer-review

45 Citations (Scopus)
124 Downloads (Pure)


We introduce a natural conjugate prior for the transition matrix of a reversible Markov chain. This allows estimation and testing. The prior arises from random walk with reinforcement in the same way the Dirichlet prior arises from Pólya’s urn. We give closed form normalizing constants, a simple method of simulation from the posterior and a characterization along the lines of W. E. Johnson’s characterization of the Dirichlet prior.
Original languageEnglish
Pages (from-to)1270-1292
JournalThe Annals of Statistics
Issue number3
Publication statusPublished - 2006


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