Strong ergodicity for continuous-time Markov chains-Reference-Cited by-同舟云学术

Strong ergodicity for continuous-time Markov chains

Published:1978-12 Issue:4 Volume:15 Page:699-706
ISSN:0021-9002
Container-title:Journal of Applied Probability
language:en
Short-container-title:Journal of Applied Probability

Author:

Isaacson Dean,Arnold Barry

Abstract

The concept of strong ergodicity for discrete-time homogeneous Markov chains has been characterized in several ways (Dobrushin (1956), Lin (1975), Isaacson and Tweedie (1978)). In this paper the characterization using mean visit times (Huang and Isaacson (1977)) is extended to continuous-time Markov chains. From this it follows that for a certain subclass of continuous-time Markov chains, X(t), is strongly ergodic if and only if the associated embedded chain is Cesaro strongly ergodic.

Publisher

Cambridge University Press (CUP)

Subject

Statistics, Probability and Uncertainty,General Mathematics,Statistics and Probability

Reference10 articles.

1. The convergence of Cesaro averages for certain nonstationary Markov chains

2. Central Limit Theorem for Nonstationary Markov Chains. I

3. Strongly ergodic Markov chains and rates of convergence using spectral conditions

4. Criteria for strong ergodicity of Markov chains

5. Uniform coupling of non-homogeneous Markov chains

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