Subgeometric Ergodicity of Strong Markov Processes

We derive sufficient conditions for subgeometric ƒ-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 ƒ-ergodicity in terms of a drift condition on the generator....

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Veröffentlicht in:	The Annals of applied probability 2005-05, Vol.15 (2), p.1565-1589
Hauptverfasser:	Fort, G., Roberts, G. O.
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Sprache:	eng
Schlagworte:	60J25 60J60 60K30 Density drift criterion Ergodic theory Langevin diffusions Markov chains Markov processes Mathematical functions Mathematical theorems Perceptron convergence procedure Polynomials Semigroups Skeleton storage models subgeometric f-ergodicity
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description	We derive sufficient conditions for subgeometric ƒ-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 ƒ-ergodicity in terms of a drift condition on the generator. Applications to specific processes are considered, including Langevin tempered diffusions on $R^{n}$ and storage models.
doi_str_mv	10.1214/105051605000000115
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O.</creatorcontrib><title>Subgeometric Ergodicity of Strong Markov Processes</title><title>The Annals of applied probability</title><description>We derive sufficient conditions for subgeometric ƒ-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 ƒ-ergodicity in terms of a drift condition on the generator. 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subjects	60J25 60J60 60K30 Density drift criterion Ergodic theory Langevin diffusions Markov chains Markov processes Mathematical functions Mathematical theorems Perceptron convergence procedure Polynomials Semigroups Skeleton storage models subgeometric f-ergodicity
title	Subgeometric Ergodicity of Strong Markov Processes
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