Subgeometric rates of convergence of f-ergodic strong Markov processes
Statistics Theory
2007-06-13 v1 Statistics Theory
Abstract
We provide a condition for f-ergodicity of strong Markov processes at a subgeometric rate. This condition is couched in terms of a supermartingale property for a functional of the Markov process. Equivalent formulations in terms of a drift inequality on the extended generator and on the resolvent kernel are given. Results related to (f,r)-regularity and to moderate deviation principle for integral (bounded) functional are also derived. Applications to specific processes are considered, including elliptic stochastic differential equation, Langevin diffusions, hypoelliptic stochastic damping Hamiltonian system and storage models.
Keywords
Cite
@article{arxiv.math/0605791,
title = {Subgeometric rates of convergence of f-ergodic strong Markov processes},
author = {Randal Douc and Gersende Fort and Arnaud Guillin},
journal= {arXiv preprint arXiv:math/0605791},
year = {2007}
}