Journal of the Korean Statistical Society

The Korean Statistical Society (한국통계학회)
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Asymptotically Adimissible and Minimax Estimators of the Unknown Mean

  • Andrew L. Rukhin (Department of Mathematics and Statistics, UMBC, Baltimore, MD 21228, USA) ;
  • Kim, Woo-Chul (Department of Computer Science and Statistics, Seoul National University, Seoul 151-742)
  • Published : 1993.12.01
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Abstract

An asymptotic estimation problem of the unknown mean is studied under a general loss function. The proof of this result is based on the asymptotic expansion of the risk function. Also conditions for second order admissibility and minimaxity of a class of estimators depending only on the sample mean are established.

Keywords

References

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