Title
A general approach to nonparametric empirical bayes estimation
Abbreviated Journal Title
Statistics
Keywords
empirical Bay estimation; posterior quadratic risk; convergence rate; reliability characteristics; RATES; MODELS; Statistics & Probability
Abstract
Let (X(1), theta(1)), (X(2), theta(2)), ..., (X(N), theta(N)), (X(N+1), theta(N+1)) be independent random vectors with each theta(i) distributed according to some unknown prior density g. Given theta(i), let X(i) have the conditional density q(i)(x/theta(i)), i=1, ..., N+1. In each pair the first component is observable, but the second is not. The objective is to estimate a known function b(theta(N+1)) of theta(N+1). A general technique for construction of empirical Bayes estimators of b(theta(N+1)) is proposed and their convergence rates are examined. The special case, when the conditional densities q(i)(x/theta), i=1, ..., N+1, are identical, is also discussed. The theory is used to estimate of some reliability characteristics of nuclear power plant equipment.
Journal Title
Statistics
Volume
29
Issue/Number
1
Publication Date
1-1-1997
Document Type
Article
Language
English
First Page
61
Last Page
80
WOS Identifier
ISSN
0233-1888
Recommended Citation
"A general approach to nonparametric empirical bayes estimation" (1997). Faculty Bibliography 1990s. 2050.
https://stars.library.ucf.edu/facultybib1990/2050
Comments
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