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September, 1985 Using Empirical Partially Bayes Inference for Increased Efficiency
Bruce G. Lindsay
Ann. Statist. 13(3): 914-931 (September, 1985). DOI: 10.1214/aos/1176349646

Abstract

Empirical partially Bayes methods are considered as a means of improving efficiency in a class of problems in which the number of nuisance parameters increases to infinity. In the method used, the parameter of interest is estimated in an asymptotically unbiased way while James-Stein shrinkage is applied to the nuisance parameter estimates. When the shrinkage estimators are carefully chosen, this yields estimators generally more efficient than maximum likelihood. In the models considered, the conditional structure imposed allows construction of a simple estimator which is broadly consistent and efficient.

Citation

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Bruce G. Lindsay. "Using Empirical Partially Bayes Inference for Increased Efficiency." Ann. Statist. 13 (3) 914 - 931, September, 1985. https://doi.org/10.1214/aos/1176349646

Information

Published: September, 1985
First available in Project Euclid: 12 April 2007

zbMATH: 0601.62044
MathSciNet: MR803748
Digital Object Identifier: 10.1214/aos/1176349646

Subjects:
Primary: 62F10
Secondary: 62F12

Keywords: conditional score , Empirical Bayes , James-Stein estimators , nuisance parameters , weighted means

Rights: Copyright © 1985 Institute of Mathematical Statistics

Vol.13 • No. 3 • September, 1985
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