Exponential and uniform ergodicity of Markov processes

• 成果类型: Article
• 署名作者: Down, D; Meyn, SP; Tweedie, RL
• 署名单位: Colorado State University System; Colorado State University Fort Collins
• 刊物名称: ANNALS OF PROBABILITY
• ISSN/ISSBN: 0091-1798
• DOI: 10.1214/aop/1176987798
• 发表日期: 1995
• 页码: 1671-1691
• 关键词: continuous-time processes; recurrence; STABILITY; criteria

摘要

General characterizations of geometric convergence for Markov chains in discrete time on a general state space have been developed recently in considerable detail. Here we develop a similar theory for phi-irreducible continuous time processes and consider the following types of criteria for geometric convergence: 1. the existence of exponentially bounded hitting times on one and then all suitably ''small'' sets; 2. the existence of ''Foster-Lyapunov'' or ''drift'' conditions for any one and then all skeleton and resolvent chains; 3. the existence of drift, conditions on the extended generator (A) over tilde of the process. We use the identity (A) over tilde R(beta) = beta(R(beta) - I) connecting the extended generator and the resolvent kernels Rp to show that, under a suitable aperiodicity assumption, exponential convergence is completely equivalent to any of criteria 1-3. These conditions yield criteria for exponential convergence of unbounded as well as bounded functions of the chain. They enable us to identify the dependence of the convergence on the initial state of the chain and also to illustrate that in general some smoothing is required to ensure convergence of unbounded functions.