The Annals of Statistics

Posterior consistency of Dirichlet mixtures in density estimation

S. Ghosal,J. K. Ghosh, and R. V. Ramamoorthi

Full-text: Open access

Abstract

A Dirichlet mixture of normal densities is a useful choice for a prior distribution on densities in the problem of Bayesian density estimation. In recent years, efficient Markov chain Monte Carlo method for the computation of the posterior distribution has been developed. The method has been applied to data arising from different fields of interest. The important issue of consistency was however left open. In this paper, we settle this issue in affirmative.

Article information

Source
Ann. Statist. Volume 27, Number 1 (1999), 143-158.

Dates
First available: 5 April 2002

Permanent link to this document
http://projecteuclid.org/euclid.aos/1018031105

Mathematical Reviews number (MathSciNet)
MR1701105

Digital Object Identifier
doi:10.1214/aos/1018031105

Zentralblatt MATH identifier
0932.62043

Subjects
Primary: 62G07: Density estimation 62G20: Asymptotic properties

Keywords
Consistency Dirichlet process mixture posterior consistency posterior distribution

Citation

Ghosal, S.; Ghosh, J. K.; Ramamoorthi, R. V. Posterior consistency of Dirichlet mixtures in density estimation. The Annals of Statistics 27 (1999), no. 1, 143--158. doi:10.1214/aos/1018031105. http://projecteuclid.org/euclid.aos/1018031105.


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