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June, 1995 Exact Multivariate Bayesian Bootstrap Distributions of Moments
Mauro Gasparini
Ann. Statist. 23(3): 762-768 (June, 1995). DOI: 10.1214/aos/1176324620

Abstract

The common unknown probability law $P$ of a random sample $Y_1,\ldots, Y_n$ is assigned a Dirichlet process prior with index $\alpha$. It is shown that the posterior joint density of several moments of $P$ converges, as $\alpha(\mathbb{R})\rightarrow 0$, to a multivariate B-spline, which is, therefore, the Bayesian bootstrap joint density of the moments. The result provides the basis for possible default nonparametric Bayesian inference on unknown moments.

Citation

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Mauro Gasparini. "Exact Multivariate Bayesian Bootstrap Distributions of Moments." Ann. Statist. 23 (3) 762 - 768, June, 1995. https://doi.org/10.1214/aos/1176324620

Information

Published: June, 1995
First available in Project Euclid: 11 April 2007

zbMATH: 0838.62032
MathSciNet: MR1345198
Digital Object Identifier: 10.1214/aos/1176324620

Subjects:
Primary: 62G05
Secondary: 62P99

Rights: Copyright © 1995 Institute of Mathematical Statistics

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Vol.23 • No. 3 • June, 1995
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