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Subgeometric rates of convergence of f-ergodic strong Markov processes

  • CNRS LTCI
  • Universités de Marseille et École Centrale Marseille

Research output: Contribution to journalArticlepeer-review

Abstract

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 subgeometric 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.

Original languageEnglish
Pages (from-to)897-923
Number of pages27
JournalStochastic Processes and their Applications
Volume119
Issue number3
DOIs
Publication statusPublished - 1 Mar 2009

Keywords

  • Foster's criterion
  • Hypoelliptic diffusions
  • Langevin diffusions
  • Moderate deviations
  • Regularity
  • Resolvent
  • Storage models
  • Subgeometric ergodicity

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