Bayesian analysis of variable-order, reversible Markov chains

Abstract

We define a conjugate prior for the reversible Markov chain of order $r$. The prior arises from a partially exchangeable reinforced random walk, in the same way that the Beta distribution arises from the exchangeable Polyá urn. An extension to variable-order Markov chains is also derived. We show the utility of this prior in testing the order and estimating the parameters of a reversible Markov model.

Published in at http://dx.doi.org/10.1214/10-AOS857 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org)

References in corpus (2)

• On Prediction Using Variable Order Markov Models
• Bayesian analysis for reversible Markov chains

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