Open Access
October, 1988 Large Deviations for the Empirical Measure of a Markov Chain with an Application to the Multivariate Empirical Measure
Richard S. Ellis
Ann. Probab. 16(4): 1496-1508 (October, 1988). DOI: 10.1214/aop/1176991580

Abstract

The main theorems in this paper prove uniform large deviation properties for the empirical measure and the multivariate empirical measure of a Markov chain that takes values in a complete separable metric space. One contribution of the paper is that, in contrast to previous large deviation results for the empirical measure, we do not assume that the transition probability of the Markov chain has a density with respect to a reference measure.

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Richard S. Ellis. "Large Deviations for the Empirical Measure of a Markov Chain with an Application to the Multivariate Empirical Measure." Ann. Probab. 16 (4) 1496 - 1508, October, 1988. https://doi.org/10.1214/aop/1176991580

Information

Published: October, 1988
First available in Project Euclid: 19 April 2007

zbMATH: 0661.60043
MathSciNet: MR958199
Digital Object Identifier: 10.1214/aop/1176991580

Subjects:
Primary: 60F10

Keywords: empirical measure , entropy function , Markov chain , multivariate empirical measure , uniform large deviation property

Rights: Copyright © 1988 Institute of Mathematical Statistics

Vol.16 • No. 4 • October, 1988
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