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Admissible estimator of the eigenvalues of the variance-covariance matrix for multivariate normal distributions

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  • Sheena, Yo
  • Takemura, Akimichi

Abstract

An admissible estimator of the eigenvalues of the variance-covariance matrix is given for multivariate normal distributions with respect to the scale-invariant squared error loss.

Suggested Citation

  • Sheena, Yo & Takemura, Akimichi, 2011. "Admissible estimator of the eigenvalues of the variance-covariance matrix for multivariate normal distributions," Journal of Multivariate Analysis, Elsevier, vol. 102(4), pages 801-815, April.
    • Handle: RePEc:eee:jmvana:v:102:y:2011:i:4:p:801-815
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    References listed on IDEAS

    as
    1. Jin, Chun, 1993. "A note on simultaneous estimation of eigenvalues of a multivariate normal covariance matrix," Statistics & Probability Letters, Elsevier, vol. 16(3), pages 197-203, February.
    2. Takemura, Akimichi & Sheena, Yo, 2005. "Distribution of eigenvalues and eigenvectors of Wishart matrix when the population eigenvalues are infinitely dispersed and its application to minimax estimation of covariance matrix," Journal of Multivariate Analysis, Elsevier, vol. 94(2), pages 271-299, June.
    3. Dipak Dey, 1988. "Simultaneous estimation of eigenvalues," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 40(1), pages 137-147, March.
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