Bayesian analysis for reversible Markov chains
Statistics Theory
2007-06-13 v2 Statistics Theory
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.
Cite
@article{arxiv.math/0605582,
title = {Bayesian analysis for reversible Markov chains},
author = {Persi Diaconis and Silke W. W. Rolles},
journal= {arXiv preprint arXiv:math/0605582},
year = {2007}
}
Comments
Published at http://dx.doi.org/10.1214/009053606000000290 in the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org)