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Bayesian inference for Markov chains

Published online by Cambridge University Press:  14 July 2016

Peter Eichelsbacher*
Ruhr-Universität Bochum
Ayalvadi Ganesh*
Microsoft Research
Postal address: Fakultät für Mathematik, Ruhr-Universität Bochum, NA 3/68, D-44780 Bochum, Germany. Email address:
∗∗ Postal address: Microsoft Research, 7 J. J. Thomson Avenue, Cambridge CB3 0FB, UK.


We consider the estimation of Markov transition matrices by Bayes’ methods. We obtain large and moderate deviation principles for the sequence of Bayesian posterior distributions.

MSC classification

Research Papers
Copyright © Applied Probability Trust 2002 

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Research supported by ARC Grant 880 from the Anglo-German foundation.


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