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Further results on estimation of covariance matrix

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  • Xu, Kai
  • He, Daojiang

Abstract

This paper considers the problem of estimating a covariance matrix under Stein’s loss. Sufficient conditions for the modified Efron–Morris estimator to be minimax under weighted quadratic loss are shown, which provide a general method for improving the estimator of the covariance matrix.

Suggested Citation

  • Xu, Kai & He, Daojiang, 2015. "Further results on estimation of covariance matrix," Statistics & Probability Letters, Elsevier, vol. 101(C), pages 11-20.
    • Handle: RePEc:eee:stapro:v:101:y:2015:i:c:p:11-20
    DOI: 10.1016/j.spl.2015.02.022
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    References listed on IDEAS

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    1. Haff, L. R., 1979. "An identity for the Wishart distribution with applications," Journal of Multivariate Analysis, Elsevier, vol. 9(4), pages 531-544, December.
    2. Bilodeau, Martin & Kariya, Takeaki, 1989. "Minimax estimators in the normal MANOVA model," Journal of Multivariate Analysis, Elsevier, vol. 28(2), pages 260-270, February.
    3. Tsukuma, Hisayuki & Kubokawa, Tatsuya, 2007. "Methods for improvement in estimation of a normal mean matrix," Journal of Multivariate Analysis, Elsevier, vol. 98(8), pages 1592-1610, September.
    4. Konno, Yoshihiko, 1991. "On estimation of a matrix of normal means with unknown covariance matrix," Journal of Multivariate Analysis, Elsevier, vol. 36(1), pages 44-55, January.
    5. Konno, Y., 1995. "Estimation of a Normal Covariance Matrix with Incomplete Data under Stein's Loss," Journal of Multivariate Analysis, Elsevier, vol. 52(2), pages 308-324, February.
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