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dc.contributor.authorDouc, Randal*
dc.contributor.authorRobert, Christian P.*
dc.date.accessioned2010-02-25T09:52:22Z
dc.date.available2010-02-25T09:52:22Z
dc.date.issued2011
dc.identifier.urihttps://basepub.dauphine.fr/handle/123456789/3578
dc.language.isoenen
dc.subjectMetropolis-Hastings algorithmen
dc.subjectcentral limit theoremen
dc.subjectMarkov Chain Monte Carlo (MCMC)en
dc.subjectconditioningen
dc.subjectvariance reductionen
dc.subject.ddc519en
dc.subject.classificationjelC15en
dc.titleA vanilla Rao-Blackwellisation of Metropolis-Hastings algorithmsen
dc.typeArticle accepté pour publication ou publié
dc.description.abstractenCasella and Robert (1996) presented a general Rao--Blackwellisation principle for accept-reject and Metropolis-Hastings schemes that leads to significant decreases in the variance of the resulting estimators, but at a high cost in computing and storage. Adopting a completely different perspective, we introduce instead a universal scheme that guarantees variance reductions in all Metropolis-Hastings~based estimators while keeping the computing cost under control. We establish a central limit theorems for the improved estimators and illustrate their performances on toy examples.en
dc.relation.isversionofjnlnameAnnals of Statistics
dc.relation.isversionofjnlvol39
dc.relation.isversionofjnlissue1
dc.relation.isversionofjnldate2011
dc.relation.isversionofjnlpages261-277
dc.relation.isversionofdoihttp://dx.doi.org/10.1214/10-AOS838
dc.identifier.urlsitehttp://arxiv.org/abs/0904.2144v5en
dc.description.sponsorshipprivateouien
dc.relation.isversionofjnlpublisherInstitute of Mathematical Statistics
dc.subject.ddclabelProbabilités et mathématiques appliquéesen
hal.person.labIds89901$$$638*
hal.person.labIds60$$$2579*


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