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).
Cite this paper
S. Assoudou and B. Essebbar, "Note on the Linearity of Bayesian Estimates in the Dependent Case," Applied Mathematics
, Vol. 5 No. 1, 2014, pp. 47-54. doi: 10.4236/am.2014.51006
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 T. C. Lee, G. G. Judge and A. Zellner, “Maximum Likelihood and Bayesian Estimation of Transition Probabilities,” JASA, Vol. 63, No. 324, 1968, pp. 1162-1179.
 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.
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