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Bayesian analysis for reversible Markov chains. (English) Zbl 1118.62085

Summary: We introduce a natural conjugate prior for the transition matrix of a reversible Markov chain. This allows estimation and testing. The prior arises from a random walk with reinforcement in the same way the Dirichlet prior arises from the Pólya 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 [see S. L. Zabell, Ann. Stat. 10, 1091–1099 (1982; Zbl 0512.62007); J. Theor. Probab. 8, No. 1, 175–178 (1995; Zbl 0814.60029)].

MSC:

62M02 Markov processes: hypothesis testing
62F15 Bayesian inference
05C90 Applications of graph theory
60J10 Markov chains (discrete-time Markov processes on discrete state spaces)
62C10 Bayesian problems; characterization of Bayes procedures

References:

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