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A sequence of improvements over the James-Stein estimator

Author

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  • Guo, Ying (Ingrid) Yueh
  • Pal, Nabendu

Abstract

In this article, we consider the problem of estimating a p-variate (p >= 3) normal mean vector in a decision-theoretic setup. Using a simple property of the noncentral chi-square distribution, we have produced a sequence of smooth estimators dominating the James-Stein estimator and each improved estimator is better than the previous one. It is also shown by using a technique of [5]. J. Multivariate Anal.36 121-126) that our smooth estimators can be dominated by non-smooth estimators.

Suggested Citation

  • Guo, Ying (Ingrid) Yueh & Pal, Nabendu, 1992. "A sequence of improvements over the James-Stein estimator," Journal of Multivariate Analysis, Elsevier, vol. 42(2), pages 302-317, August.
    • Handle: RePEc:eee:jmvana:v:42:y:1992:i:2:p:302-317
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    Citations

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    Cited by:

    1. Serdobolskii, V. I., 2005. "Matrix shrinkage of high-dimensional expectation vectors," Journal of Multivariate Analysis, Elsevier, vol. 92(2), pages 281-297, February.
    2. Yuzo Maruyama & William Strawderman, 2005. "Necessary conditions for dominating the James-Stein estimator," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 57(1), pages 157-165, March.
    3. Pal, Nabendu & Ling, Chiahua, 1995. "Improved minimax estimation of powers of the variance of a multivariate normal distribution under the entropy loss function," Statistics & Probability Letters, Elsevier, vol. 24(3), pages 205-211, August.

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