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dc.contributor.authorArbel, Julyan
dc.date.accessioned2010-07-22T14:13:23Z
dc.date.available2010-07-22T14:13:23Z
dc.date.issued2010
dc.identifier.urihttps://basepub.dauphine.fr/handle/123456789/4639
dc.language.isoenen
dc.subjectSieve prioren
dc.subjectSoboleven
dc.subject.ddc519en
dc.subject.classificationjelC11en
dc.titleBayesian Adaptive Estimation Using a Sieve Prioren
dc.typeCommunication / Conférence
dc.description.abstractenWe study the Bayes estimation of an infinite dimensional parameter from a Sobolev smoothness class. We propose a family of sieve priors whose resulting Bayes estimators are adaptive optimal, both in posterior concentration rate and in risk convergence for the inherent distance of the model, denoted dn (e.g. the Hellinger distance). This result is applied to several examples, including white noise model, regression function and density model.en
dc.description.sponsorshipprivateouien
dc.subject.ddclabelProbabilités et mathématiques appliquéesen
dc.relation.conftitle9th Valencia International Meeting on Bayesian Statistics - 2010 World Meeting of the International Society for Bayesian Analysisen
dc.relation.confdate2010-06
dc.relation.confcityBenidormen
dc.relation.confcountryEspagneen


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