S. Assoudou and B. Essebbar, “A Bayesian Model for Markov Chains via Jeffreys’ Prior,” Department of Mathematics and Computer Sciences, Faculté des Sciences of Rabat, Morocco, 2001.
has been cited by the following article:
TITLE: Note on the Linearity of Bayesian Estimates in the Dependent Case
AUTHORS: Souad Assoudou, Belkheir Essebbar
KEYWORDS: Bayes Estimator; Maximum Likelihood Estimator; Markov Chain; Transition Probabilities; Jeffreys’ Prior; Multivariate Beta Prior; MCMC
JOURNAL NAME: Applied Mathematics, Vol.5 No.1, January 2, 2014
ABSTRACT: This work deals with the relationship between the Bayesian and the maximum likelihood estimators in case of dependent observations. In case of Markov chains, we show that the Bayesian estimator of the transition probabilities is a linear function of the maximum likelihood estimator (MLE).