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dc.contributor.authorRobert, Christian P.
dc.date.accessioned2010-04-29T14:52:19Z
dc.date.available2010-04-29T14:52:19Z
dc.date.issued2010
dc.identifier.urihttps://basepub.dauphine.fr/handle/123456789/4054
dc.descriptionLe lien HAL conduit à une version révisée de ce chapitre.
dc.language.isoenen
dc.subjectBayesian Statisticsen
dc.subject.ddc519en
dc.subject.classificationjelC11en
dc.titleBayesian computational methods (2e ed.)en
dc.typeChapitre d'ouvrage
dc.description.abstractenIn this chapter, we will first present the most standard computational challenges met in Bayesian Statistics, focussing primarily on mixture estimation and on model choice issues, and then relate these problems with computational solutions. Of course, this chapter is only a terse introduction to the problems and solutions related to Bayesian computations. For more complete references, see Robert and Casella (2004, 2009), or Marin and Robert (2007), among others. We also restrain from providing an introduction to Bayesian Statistics per se and for comprehensive coverage, address the reader to Robert (2007), (again) among others.en
dc.identifier.citationpages719-766
dc.relation.ispartoftitleHandbook of Computational Statisticsen
dc.relation.ispartofeditorHärdle, Wolfgang
dc.relation.ispartofeditorGentle, James
dc.relation.ispartofeditorMori, Yuichi
dc.relation.ispartofpublnameSpringeren
dc.relation.ispartofpublcityBerlinen
dc.relation.ispartofdate2010
dc.relation.ispartofpages1070
dc.identifier.urlsitehttp://hal.archives-ouvertes.fr/hal-00473019/fr/en
dc.description.sponsorshipprivateouien
dc.subject.ddclabelProbabilités et mathématiques appliquéesen
dc.relation.ispartofisbn978-3-540-40464-4


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