IMPROVING ON THE JAMES-STEIN POSITIVE-PART ESTIMATOR
成果类型：
Article
署名作者：
SHAO, PYS; STRAWDERMAN, WE
刊物名称：
ANNALS OF STATISTICS
ISSN/ISSBN：
0090-5364
DOI：
10.1214/aos/1176325640
发表日期：
1994
页码：
1517-1538
关键词：
摘要：
The purpose of this paper is to give an explicit estimator dominating the positive-part James-Stein rule. The James-Stein estimator improves on the ''usual'' estimator X of a multivariate normal mean vector theta if the dimension p of the problem is at least 3. It has been known since at least 1964 that the positive-part version of this estimator improves on the James-Stein estimator. Brown's 1971 results imply that the positive-part version is itself inadmissible although this result was assumed to be true much earlier. Explicit improvements, however, have not previously been found; indeed, 1988 results of Beck and of Brown imply that no estimator dominating the positive-part estimator exists whose unbiased estimator of risk is uniformly smaller than that of the positive-part estimator.
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