Bayesian robustness and the stein effect


Journal Article

In simultaneous estimation of normal means, it is shown that through use of the Stein effect surprisingly large gains of a Bayesian nature can be achieved, at little or no cost, if the prior information is misspecified. This provides a justification, in terms of robustness with respect to mis-specification of the prior, for employing the Stein effect, even when combining a priori independent problems (i.e., problems in which no empirical Bayes effects are obtainable). To study this issue, a class of minimax estimators that closely mimic the conjugate prior Bayes estimators is introduced. © 1982 Taylor & Francis Group, LLC.

Full Text

Duke Authors

Cited Authors

  • Berger, J

Published Date

  • January 1, 1982

Published In

Volume / Issue

  • 77 / 378

Start / End Page

  • 358 - 368

Electronic International Standard Serial Number (EISSN)

  • 1537-274X

International Standard Serial Number (ISSN)

  • 0162-1459

Digital Object Identifier (DOI)

  • 10.1080/01621459.1982.10477818

Citation Source

  • Scopus