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March, 1994 A Unified Approach to Improving Equivariant Estimators
Tatsuya Kubokawa
Ann. Statist. 22(1): 290-299 (March, 1994). DOI: 10.1214/aos/1176325369

Abstract

In the point and interval estimation of the variance of a normal distribution with an unknown mean, the best affine equivariant estimators are dominated by Stein's truncated and Brewster and Zidek's smooth procedures, which are separately derived. This paper gives a unified approach to this problem by using a simple definite integral and provides a class of improved procedures in both point and interval estimation of powers of the scale parameter of normal, lognormal, exponential and Pareto distributions. Finally, the same method is applied to the improvement on the James-Stein rule in the simultaneous estimation of a multinormal mean.

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Tatsuya Kubokawa. "A Unified Approach to Improving Equivariant Estimators." Ann. Statist. 22 (1) 290 - 299, March, 1994. https://doi.org/10.1214/aos/1176325369

Information

Published: March, 1994
First available in Project Euclid: 11 April 2007

zbMATH: 0816.62021
MathSciNet: MR1272084
Digital Object Identifier: 10.1214/aos/1176325369

Subjects:
Primary: 62C99
Secondary: 62F11, 62F25

Rights: Copyright © 1994 Institute of Mathematical Statistics

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Vol.22 • No. 1 • March, 1994
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