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dc.contributor.authorCasella, George
dc.contributor.authorRobert, Christian P.
dc.contributor.authorWells, Martin T.
dc.date.accessioned2011-07-25T15:51:58Z
dc.date.available2011-07-25T15:51:58Z
dc.date.issued2004
dc.identifier.urihttps://basepub.dauphine.fr/handle/123456789/6781
dc.language.isoenen
dc.subjectMonte Carlo methodsen
dc.subjectAccept-Rejecten
dc.subjectstopping ruleen
dc.subjectrecyclingen
dc.subjectuniform variableen
dc.subject.ddc519en
dc.titleGeneralized Accept-Reject Sampling Schemesen
dc.typeChapitre d'ouvrage
dc.description.abstractenThis paper extends the Accept-Reject algorithm to allow the proposal distribution to change at each iteration. We first establish a necessary and sufficient condition for this generalized Accept-Reject algorithm to be valid, and then show how the resulting estimator can be improved by Rao-Blackwellization. An application of these results is to the perfect sampling technique of Fill (1998), An interruptible algorithm for perfect sampling via Markov chains, which is a generalized Accept-Reject algorithm.en
dc.identifier.citationpages342-347en
dc.relation.ispartofseriestitleLecture Notes Monograph Series
dc.relation.ispartofseriesnumber45
dc.relation.ispartoftitleA Festschrift for Herman Rubinen
dc.relation.ispartofeditorRubin, Herman
dc.relation.ispartofeditorDasGupta, Anirban
dc.relation.ispartofpublnameInstitute of Mathematical Statisticsen
dc.relation.ispartofpublcityBeachwood (Ohio)en
dc.relation.ispartofdate2004
dc.relation.ispartofpages417en
dc.relation.ispartofurlhttp://projecteuclid.org/euclid.lnms/1196285369en
dc.description.sponsorshipprivateouien
dc.subject.ddclabelProbabilités et mathématiques appliquéesen
dc.relation.ispartofisbn0-940600-61-7en
dc.identifier.doihttp://dx.doi.org/10.1214/lnms/1196285403


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