Bayesian analysis for reversible Markov chains

Preprint

1 August 2006

preprint
Published by arXiv in arXiv

https://doi.org/10.48550/arXiv.math/0605582

Abstract

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 P\'{o}lya'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.

Keywords

REVERSIBLE MARKOV CHAINS
BAYESIAN ANALYSIS
DIRICHLET PRIOR
PRIOR ARISES
RANDOM WALK
JOHNSON'S
WALK

All Related Versions

Version 1, 2006-05-22, ArXiv
Version 2, 2006-08-01, ArXiv
Published version: The Annals of Statistics, 34 (3).

This publication has 0 references indexed in Scilit: