Evaluation of empirical Bayes estimators for small numbers of past samples

Published

Journal Article

SUMMARY: The usual technique for evaluating the performance of empirical Bayes estimators for small numbers, N, of past observations is to compare by Monte Carlo techniques the global risk for the empirical Bayes estimator to the risk obtained for some optimal non-Bayes estimator δ. Here it is shown, under fairly general conditions, that if the prior variance ß2 is small relative to the Bayes risk of δ, and if N≠ 0, then one can always find an estimator that is better than δ, regardless of the form of the prior G or the magnitude of N. © 1971 Oxford University Press.

Full Text

Duke Authors

Cited Authors

  • George, SL

Published Date

  • April 1, 1971

Published In

Volume / Issue

  • 58 / 1

Start / End Page

  • 244 -

International Standard Serial Number (ISSN)

  • 0006-3444

Digital Object Identifier (DOI)

  • 10.1093/biomet/58.1.244

Citation Source

  • Scopus