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hal.structure.identifierInstitut de Mathématiques de Bordeaux [IMB]
hal.structure.identifierQuality control and dynamic reliability [CQFD]
dc.contributor.authorBERCU, Bernard
hal.structure.identifierInstitut de Mathématiques de Bordeaux [IMB]
hal.structure.identifierAdvanced Learning Evolutionary Algorithms [ALEA]
dc.contributor.authorDEL MORAL, Pierre
hal.structure.identifierDept of Statistics & Dept of Computer Science
hal.structure.identifierDepartment of Statistics [Vancouver] [UBC Statistics]
dc.contributor.authorDOUCET, Arnaud
dc.date.issued2012
dc.identifier.issn0304-4149
dc.description.abstractEnWe present a functional central limit theorem for a general class of interacting Markov chain Monte Carlo interpretations of discrete generation measure-valued equations. The path space models associated with these stochastic processes belong to the class of nonlinear Markov chains interacting with their empirical occupation measures. We develop an original theoretical analysis based on resolvent operators and semigroup techniques to analyze the fluctuation of their occupation measures around their limiting value. We also present a set of simple regularity conditions that applies to interacting Markov chain Monte Carlo models on path spaces, yielding what seems to be the first fluctuation theorems for this class of self-interacting models.
dc.language.isoen
dc.publisherElsevier
dc.title.enFluctuations of Interacting Markov Chain Monte Carlo Models
dc.typeArticle de revue
dc.subject.halMathématiques [math]/Probabilités [math.PR]
bordeaux.journalStochastic Processes and their Applications
bordeaux.page1304-1331
bordeaux.volume122
bordeaux.issue4
bordeaux.peerReviewedoui
bordeaux.type.reportrr
hal.identifierinria-00227536
hal.version1
hal.popularnon
hal.audienceInternationale
hal.origin.linkhttps://hal.archives-ouvertes.fr//inria-00227536v1
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