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

Stephen G. Walker, Antonio Lijoi, Igor Prünster

The Annals of Statistics · 2007 · Volume 35 · Issue 2

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.

Keywords

62F15, 62G07, 62G20, Hellinger consistency, mixture of Dirichlet process, posterior distribution, rates of convergence

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