International Journal of Mathematics and Mathematical Sciences
Volume 2004 (2004), Issue 8, Pages 421-429
doi:10.1155/S0161171204202319
A Bayesian model for binary Markov chains
Department of Mathematics and Computer Sciences, Faculty of Sciences, Avenue Ibn Batouta, Rabat BP 1014, Morocco
Received 20 February 2002
Copyright © 2004 Souad Assoudou and Belkheir Essebbar. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
This note is concerned with Bayesian estimation of the transition probabilities of a binary Markov chain observed from heterogeneous individuals. The model is founded on the Jeffreys' prior which allows for transition probabilities to be correlated. The Bayesian estimator is approximated by means of Monte Carlo Markov chain (MCMC) techniques. The performance of the Bayesian estimates is illustrated by analyzing a small simulated data set.