ON THE LARGE DEVIATION RATE FUNCTION FOR THE EMPIRICAL MEASURES OF REVERSIBLE JUMP MARKOV PROCESSES

被引:8
作者
Dupuis, Paul [1 ]
Liu, Yufei [2 ]
机构
[1] Brown Univ, Div Appl Math, Providence, RI 02912 USA
[2] Google Inc, Mountain View, CA 94043 USA
关键词
Large deviation rate function; reversible Markov process; pure jump process; empirical measure; weak convergence; ASYMPTOTIC EVALUATION; PROCESS EXPECTATIONS; LARGE TIME;
D O I
10.1214/13-AOP883
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
The large deviations principle for the empirical measure for both continuous and discrete time Markov processes is well known. Various expressions are available for the rate function, but these expressions are usually as the solution to a variational problem, and in this sense not explicit. An interesting class of continuous time, reversible processes was identified in the original work of Donsker and Varadhan for which an explicit expression is possible. While this class includes many (reversible) processes of interest, it excludes the case of continuous time pure jump processes, such as a reversible finite state Markov chain. In this paper, we study the large deviations principle for the empirical measure of pure jump Markov processes and provide an explicit formula of the rate function under reversibility.
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页码:1121 / 1156
页数:36
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