Subgeometric rates of convergence of f-ergodic strong Markov processes

被引：106

作者：

Douc, Randal ^{[3
]}

Fort, Gersende ^{[4
]}

Guillin, Arnaud ^{[1
,2
]}

机构：

[1] Ecole Cent Marseille, F-13453 Marseille 13, France

[2] CNRS, LATP, UMR 6632, F-13453 Marseille 13, France

[3] Ecole Polytech, CMAP, F-91128 Palaiseau, France

[4] LTCI, CNRS, F-75634 Paris 13, France

来源：

STOCHASTIC PROCESSES AND THEIR APPLICATIONS | 2009年 / 119卷 / 03期

关键词：

Subgeometric ergodicity; Regularity; Foster's criterion; Resolvent; Moderate deviations; Langevin diffusions; Hypoelliptic diffusions; Storage models; MODERATE DEVIATIONS; STABILITY; INEQUALITIES;

D O I：

10.1016/j.spa.2008.03.007

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：

We provide a condition in terms of a supermartingale property for a functional of the Markov process, which implies (a) f-ergodicity of strong Markov processes at a suhgeometric rate, and (b) a moderate deviation principle for an integral (bounded) functional. An equivalent condition in terms of a drift inequality on the extended generator is also given. Results related to (f, r)-regularity of the process, of some skeleton chains and of the resolvent chain are also derived. Applications to specific processes are considered, including elliptic stochastic differential equations, Langevin diffusions, hypoelliptic stochastic damping Hamiltonian systems and storage models. (C) 2008 Elsevier B.V. All rights reserved.

引用

页码：897 / 923

页数：27

共 33 条

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