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dc.contributor.authorSalomond, Jean-Bernard
HAL ID: 10173
dc.date.accessioned2013-12-02T15:09:09Z
dc.date.available2013-12-02T15:09:09Z
dc.date.issued2014
dc.identifier.urihttps://basepub.dauphine.fr/handle/123456789/12223
dc.language.isoenen
dc.subjectBayesian Nonparametricen
dc.subjectNonparametric hypothesis testingen
dc.subjectNonparametric regressionen
dc.subjectAsymptotic propertiesen
dc.subject.ddc519en
dc.titleAdaptive Bayes Test for Monotonicityen
dc.typeCommunication / Conférence
dc.description.abstractenWe study the asymptotic behavior of a Bayesian nonparametric test of qualitative hypotheses. More precisely, we focus on the problem of testing monotonicity of a regression function. Even if some results are known in the frequentist framework, no Bayesian testing procedure has been proposed; at least none has been studied theoretically. This paper proposes a procedure that is straightforward to implement, which is a great advantage compared to those proposed in the literature.en
dc.identifier.citationpages29-33en
dc.relation.ispartofseriestitleSpringer Proceedings in Mathematics & Statisticsen
dc.relation.ispartofseriesnumber63en
dc.relation.ispartoftitleThe Contribution of Young Researchers to Bayesian Statistics. Proceedings of BAYSM2013en
dc.relation.ispartofeditorLanzarone, Ettore
dc.relation.ispartofeditorIeva, Francesca
dc.relation.ispartofpublnameSpringeren
dc.relation.ispartofpublcityBerlinen
dc.relation.ispartofdate2014
dc.relation.ispartofpages214en
dc.relation.ispartofurlhttp://dx.doi.org/10.1007/978-3-319-02084-6en
dc.identifier.urlsitehttp://arxiv.org/abs/1303.6466v1en
dc.subject.ddclabelProbabilités et mathématiques appliquéesen
dc.relation.ispartofisbn978-3-319-02083-9en
dc.relation.conftitleBAyesian Young Statistician Meeting (BAYSM) 2013en
dc.relation.confdate2013-06
dc.relation.confcityMilanen
dc.relation.confcountryItalieen
dc.relation.forthcomingnonen
dc.identifier.doihttp://dx.doi.org/10.1007/978-3-319-02084-6_7en


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