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dc.contributor.authorRobert, Christian P.
dc.contributor.authorMarin, Jean-Michel
dc.contributor.authorIacobucci, Alessandra
dc.date.accessioned2009-07-07T09:54:01Z
dc.date.available2009-07-07T09:54:01Z
dc.date.issued2010
dc.identifier.urihttps://basepub.dauphine.fr/handle/123456789/872
dc.language.isoenen
dc.subjectImportance sampling mixtureen
dc.subjectAdaptive Monte Carloen
dc.subjectPopulation Monte Carloen
dc.subjectMultimodalityen
dc.subjectMixture of distributionsen
dc.subjectRandom walken
dc.subject.ddc519en
dc.subject.classificationjelC15
dc.titleOn variance stabilisation in population Monte Carlo by double Rao-Blackwellisationen
dc.typeArticle accepté pour publication ou publié
dc.contributor.editoruniversityotherINRIA – Université Paris Sud - Paris XI;France
dc.contributor.editoruniversityotherINSEE;France
dc.description.abstractenPopulation Monte Carlo has been introduced as a sequential importance sampling technique to overcome poor fit of the importance function. In this paper, we compare the performances of the original Population Monte Carlo algorithm with a modified version that eliminates the influence of the transition particle via a double Rao-Blackwellisation. This modification is shown to improve the exploration of the modes through an large simulation experiment on posterior distributions of mean mixtures of distributions.en
dc.relation.isversionofjnlnameComputational Statistics and Data Analysis
dc.relation.isversionofjnlvol54
dc.relation.isversionofjnlissue3
dc.relation.isversionofjnldate2010-03
dc.relation.isversionofjnlpages698-710
dc.relation.isversionofdoihttp://dx.doi.org/10.1016/j.csda.2008.09.020
dc.identifier.urlsitehttp://hal.inria.fr/inria-00260141/en/en
dc.description.sponsorshipprivatenonen
dc.relation.isversionofjnlpublisherElsevier
dc.subject.ddclabelProbabilités et mathématiques appliquéesen


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