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Approximate Bayesian Computational methods

hal.structure.identifier
dc.contributor.authorMarin, Jean-Michel
HAL ID: 9121
ORCID: 0000-0001-7451-9719		*
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dc.contributor.authorPudlo, Pierre*
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dc.contributor.authorRobert, Christian P.*
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dc.contributor.authorRyder, Robin J.*
dc.date.accessioned2011-03-02T15:25:32Z
dc.date.available2011-03-02T15:25:32Z
dc.date.issued2012
dc.identifier.urihttps://basepub.dauphine.fr/handle/123456789/5724
dc.language.isoenen
dc.subjectlikelihood-free methodsen
dc.subjectBayesian statisticsen
dc.subjectABC Methodologyen
dc.subjectDIYABCen
dc.subjectBayesian model chanceen
dc.subject.ddc519en
dc.subject.classificationjelC15en
dc.subject.classificationjelC11en
dc.titleApproximate Bayesian Computational methodsen
dc.typeArticle accepté pour publication ou publié
dc.contributor.editoruniversityotherInstitut Universitaire de France (IUF) Ministère de l'Enseignement Supérieur et de la Recherche Scientifique;France
dc.contributor.editoruniversityotherInstitut de Mathématiques et de Modélisation de Montpellier (I3M) CNRS : UMR5149 – Université Montpellier II - Sciences et Techniques du Languedoc;France
dc.contributor.editoruniversityotherCentre de Recherche en Économie et Statistique (CREST) INSEE – École Nationale de la Statistique et de l'Administration Économique;France
dc.description.abstractenAlso known as likelihood-free methods, approximate Bayesian computational (ABC) methods have appeared in the past ten years as the most satisfactory approach to untractable likelihood problems, first in genetics then in a broader spectrum of applications. However, these methods suffer to some degree from calibration difficulties that make them rather volatile in their implementation and thus render them suspicious to the users of more traditional Monte Carlo methods. In this survey, we study the various improvements and extensions made to the original ABC algorithm over the recent years.en
dc.relation.isversionofjnlnameStatistics and Computing
dc.relation.isversionofjnlvol22
dc.relation.isversionofjnlissue6
dc.relation.isversionofjnldate2012
dc.relation.isversionofjnlpages1167-1180
dc.relation.isversionofdoihttp://dx.doi.org/10.1007/s11222-011-9288-2
dc.identifier.urlsitehttps://arxiv.org/abs/1101.0955en
dc.description.sponsorshipprivateouien
dc.relation.isversionofjnlpublisherSpringer
dc.subject.ddclabelProbabilités et mathématiques appliquéesen
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