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March, 1975 Approximate Bayes Solutions to Some Nonparametric Problems
M. Goldstein
Ann. Statist. 3(2): 512-517 (March, 1975). DOI: 10.1214/aos/1176343081

Abstract

The problem of making inferences about real functions of a probability distribution of unknown form is examined in a Bayesian nonparameteric framework. With respect to a general quadratic loss function, Bayes estimates within the class of linear combinations of a given set of functions on the sample space are obtained for general functions on the distribution space. The result is then used to derive Bayes polynomial estimates of the moments of the distribution.

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M. Goldstein. "Approximate Bayes Solutions to Some Nonparametric Problems." Ann. Statist. 3 (2) 512 - 517, March, 1975. https://doi.org/10.1214/aos/1176343081

Information

Published: March, 1975
First available in Project Euclid: 12 April 2007

zbMATH: 0325.62032
MathSciNet: MR362702
Digital Object Identifier: 10.1214/aos/1176343081

Subjects:
Primary: 62C10
Secondary: 62G05

Keywords: Bayes nonparametric estimation , linear approximation , polynomial estimators for population moments

Rights: Copyright © 1975 Institute of Mathematical Statistics

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Vol.3 • No. 2 • March, 1975
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