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A Generalization of B. S. Clarke and A. R. Barron's Asymptotics of Bayes Codes for FSMX Sources
Masayuki GOTOH Toshiyasu MATSUSHIMA Shigeichi HIRASAWA
IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences
Publication Date: 1998/10/25
Print ISSN: 0916-8508
Type of Manuscript: Special Section PAPER (Special Section on Information Theory and Its Applications)
Category: Source Coding
Bayes code, source coding, universal coding, universal modeling,
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We shall generalize B. S. Clarke and A. R. Barron 's analysis of the Bayes method for the FSMX sources. The FSMX source considered here is specified by the set of all states and its parameter value. At first, we show the asymptotic codelengths of individual sequences of the Bayes codes for the FSMX sources. Secondly, we show the asymptotic expected codelengths. The Bayesian posterior density and the maximum likelihood estimator satisfy asymptotic normality for the finite ergodic Markov source, and this is the key of our analysis.