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A Unified and Broadened Class of Admissible Minimax Estimators of a Multivariate Normal Mean


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  • Maruyama, Yuzo
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    The problem of estimating the mean of a multivariate normal distribution is considered. A class of admissible minimax estimators is constructed. This class includes two well-known classes of estimators, Strawderman's and Alam's. Further, this class is much broader than theirs.

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    Article provided by Elsevier in its journal Journal of Multivariate Analysis.

    Volume (Year): 64 (1998)
    Issue (Month): 2 (February)
    Pages: 196-205

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    Handle: RePEc:eee:jmvana:v:64:y:1998:i:2:p:196-205

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    Keywords: admissible; minimax; multivariate normal mean; generalized Bayes; quadratic loss;


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    1. Faith, Ray E., 1978. "Minimax Bayes estimators of a multivariate normal mean," Journal of Multivariate Analysis, Elsevier, Elsevier, vol. 8(3), pages 372-379, September.
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    Cited by:
    1. Hiroyuki Kashima, 2005. "An application of a minimax Bayes rule and shrinkage estimators to the portofolio selection problem under the Bayesian approach," Statistical Papers, Springer, Springer, vol. 46(4), pages 523-540, October.
    2. Maruyama, Yazo & Takemura, Akimichi, 2008. "Admissibility and minimaxity of generalized Bayes estimators for spherically symmetric family," Journal of Multivariate Analysis, Elsevier, Elsevier, vol. 99(1), pages 50-73, January.
    3. Maruyama, Yuzo & Strawderman, William E., 2009. "An extended class of minimax generalized Bayes estimators of regression coefficients," Journal of Multivariate Analysis, Elsevier, Elsevier, vol. 100(10), pages 2155-2166, November.
    4. Maruyama, Yuzo, 2003. "Admissible minimax estimators of a mean vector of scale mixtures of multivariate normal distributions," Journal of Multivariate Analysis, Elsevier, Elsevier, vol. 84(2), pages 274-283, February.


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