The Annals of Statistics

Bayesian analysis of variable-order, reversible Markov chains

Sergio Bacallado

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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.

Article information

Source
Ann. Statist., Volume 39, Number 2 (2011), 838-864.

Dates
First available in Project Euclid: 9 March 2011

Permanent link to this document
https://projecteuclid.org/euclid.aos/1299680956

Digital Object Identifier
doi:10.1214/10-AOS857

Mathematical Reviews number (MathSciNet)
MR2816340

Zentralblatt MATH identifier
1215.62083

Subjects
Primary: 62M02: Markov processes: hypothesis testing
Secondary: 62C10: Bayesian problems; characterization of Bayes procedures

Keywords
Reversibility reinforced random walks variable-order Markov chains Bayesian analysis conjugate priors

Citation

Bacallado, Sergio. Bayesian analysis of variable-order, reversible Markov chains. Ann. Statist. 39 (2011), no. 2, 838--864. doi:10.1214/10-AOS857. https://projecteuclid.org/euclid.aos/1299680956


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Supplemental materials

  • Supplementary material: Law of a variable-order, reinforced random walk. We provide a closed form expression for this law as a function of transition counts and suggest how it could be useful.