Estimating one of two normal means when their difference is bounded

Constance van Eeden and James V. Zidek

Statistics & Probability Letters, 2001, vol. 51, issue 3, 277-284

Abstract: In this paper, we address the problem of estimating [theta]1 when , are observed, the [sigma]j are known and [theta]1-[theta]2[less-than-or-equals, slant]c for a known constant c. Assuming the loss is squared error, we derive a generalized Bayes estimator which is admissible. It uses Y2 to achieve a uniformly smaller risk than that of the classical UMVU estimator, Y1. The proofs use a combination of Stein and Kubokawa methods.

Keywords: Estimation; Admissibility; Normal; means; Restricted; parameter; spaces; Relevance; weighting (search for similar items in EconPapers)
Date: 2001
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Citations: View citations in EconPapers (2)

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