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Subgeometric ergodicity of strong Markov processes

  • Department of Mathematics and Statistics, Lancaster University

Research output: Contribution to journalArticlepeer-review

72 Citations (Scopus)

Abstract

We derive sufficient conditions for subgeometric f-ergodicity of strongly Markovian processes. We first propose a criterion based on modulated moment of some delayed return-time to a petite set. We then formulate a criterion for polynomial f-ergodicity in terms of a drift condition on the generator. Applications to specific processes are considered, including Langevin tempered diffusions on ℝn and storage models.

Original languageEnglish
Pages (from-to)1565-1589
Number of pages25
JournalAnnals of Applied Probability
Volume15
Issue number2
DOIs
Publication statusPublished - 1 Jan 2005

Keywords

  • Drift criterion
  • Langevin diffusions
  • Markov processes
  • Storage models
  • Subgeometric f-ergodicity

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