アイテムタイプ

テクニカルレポート / Technical Report

言語

英語

キーワード

Covariance matrix, generalized variance, minimax estimation, improvement, decision theory, Stein result, Bartlett's decomposition

著者

Kubokawa Tatsuya
M. S. Srivastava

著者所属

University of Tookyo
University of Toronto

抄録

In this paper, we consider the problem of estimating the covariance matrix and the generalized variance when the observations follow a nonsingular multivariate normal distribution with unknown mean. A new method is presented to obtain a truncated estimator that utilizes the information available in the sample mean matrix and dominates the James-Stein minimax estimator. Several scale equivariant minimax estimators are also given. This method is then applied to obtain new truncated and improved estimators of the generalized variance; it also provides a new proof to the results of Shorro k and Zidek (1976)and Sinha (1976).

内容記述

Former Version: 1999-CF-52
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雑誌名

Discussion paper series. CIRJE-F

巻

2002-CF-162

発行年

2002-07

書誌レコードID

AA11450569

フォーマット

application/pdf