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On the non existence of unbiased estimators of risk for spherically symmetric distributions

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  • Fourdrinier, Dominique
  • Strawderman, William

Abstract

We study existence of unbiased estimators of risk for estimators of the location parameter of a spherically symmetric distribution, when a residual vector is available to estimate scale, under invariant quadratic loss. We show such existence often characterizes normality.

Suggested Citation

  • Fourdrinier, Dominique & Strawderman, William, 2014. "On the non existence of unbiased estimators of risk for spherically symmetric distributions," Statistics & Probability Letters, Elsevier, vol. 91(C), pages 6-13.
    • Handle: RePEc:eee:stapro:v:91:y:2014:i:c:p:6-13
    DOI: 10.1016/j.spl.2014.03.022
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    References listed on IDEAS

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    1. Fourdrinier, Dominique & Strawderman, William E., 2008. "A unified and generalized set of shrinkage bounds on minimax Stein estimates," Journal of Multivariate Analysis, Elsevier, vol. 99(10), pages 2221-2233, November.
    2. Cellier, Dominique & Fourdrinier, Dominique & Robert, Christian, 1989. "Robust shrinkage estimators of the location parameter for elliptically symmetric distributions," Journal of Multivariate Analysis, Elsevier, vol. 29(1), pages 39-52, April.
    3. Fourdrinier, Dominique & Strawderman, William E. & Wells, Martin T., 2003. "Robust shrinkage estimation for elliptically symmetric distributions with unknown covariance matrix," Journal of Multivariate Analysis, Elsevier, vol. 85(1), pages 24-39, April.
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    Cited by:

    1. Dominique Fourdrinier & William Strawderman, 2015. "Robust minimax Stein estimation under invariant data-based loss for spherically and elliptically symmetric distributions," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 78(4), pages 461-484, May.

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