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On rates of convergence for posterior distributions in infinite-dimensional models

Walker, Stephen G., Lijoi, Antonio, Prunster, Igor (2007) On rates of convergence for posterior distributions in infinite-dimensional models. Annals of Statistics, 35 (2). pp. 738-746. ISSN 0090-5364. (doi:10.1214/009053606000001361) (KAR id:2032)

Abstract

This paper introduces a new approach to the study of rates of convergence for posterior distributions. It is a natural extension of a recent approach to the study of Bayesian consistency. In particular, we improve on current rates of convergence for models including the mixture of Dirichlet process model and the random Bernstein polynomial model.

Item Type: Article
DOI/Identification number: 10.1214/009053606000001361
Uncontrolled keywords: Hellinger consistency; mixture of dirichlet process; posterior distribution; rates of convergence
Subjects: Q Science > QA Mathematics (inc Computing science) > QA276 Mathematical statistics
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Mathematics, Statistics and Actuarial Science
Depositing User: Stephen Holland
Date Deposited: 19 Dec 2007 19:24 UTC
Last Modified: 16 Nov 2021 09:40 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/2032 (The current URI for this page, for reference purposes)

University of Kent Author Information

Walker, Stephen G..

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