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

Rousseau, Judith; Mengersen, Kerrie; McVinish, Ross

Rousseau, Judith; Mengersen, Kerrie; McVinish, Ross (2005), Bayesian Mixtures of Triangular distributions with application to Goodness-of-Fit Testing. https://basepub.dauphine.fr/handle/123456789/6212

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Type

Document de travail / Working paper

Date

2005

Éditeur

Université Paris-Dauphine

Titre de la collection

Cahiers du CEREMADE

Numéro dans la collection

2005-31

Ville d’édition

Paris

Métadonnées

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Auteur(s)

Rousseau, Judith
Mengersen, Kerrie
McVinish, Ross

Résumé (EN)

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.

Mots-clés

Rate of convergence; Posterior dsitribution; Consistency; Bayesian nonparametric density estimation