Bayesian Mixtures of Triangular distributions with application to Goodness-of-Fit Testing

dc.contributor.author	Rousseau, Judith
dc.contributor.author	Mengersen, Kerrie
dc.contributor.author	McVinish, Ross
dc.date.accessioned	2011-05-09T08:56:05Z
dc.date.available	2011-05-09T08:56:05Z
dc.date.issued	2005
dc.identifier.uri	https://basepub.dauphine.fr/handle/123456789/6212
dc.language.iso	en	en
dc.subject	Rate of convergence	en
dc.subject	Posterior dsitribution	en
dc.subject	Consistency	en
dc.subject	Bayesian nonparametric density estimation	en
dc.subject.ddc	519	en
dc.title	Bayesian Mixtures of Triangular distributions with application to Goodness-of-Fit Testing	en
dc.type	Document de travail / Working paper
dc.description.abstracten	Two forms of mixtures of triangular distributions are considered as an alternative to the Bernstein polynomials for Bayesian nonparametric density estimation on [0, 1]. Conditions for weak and strong consistency of the posterior distribution and a rate of convergence are established. This class of priors is applied to the problem of testing a parametric family against a nonparametric alternative.	en
dc.publisher.name	Université Paris-Dauphine	en
dc.publisher.city	Paris	en
dc.identifier.citationpages	45	en
dc.relation.ispartofseriestitle	Cahiers du CEREMADE	en
dc.relation.ispartofseriesnumber	2005-31	en
dc.description.sponsorshipprivate	oui	en
dc.subject.ddclabel	Probabilités et mathématiques appliquées	en

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