Large-sample estimation strategies for eigenvalues of a Wishart matrix |
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Authors: | S E Ahmed |
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Institution: | (1) Department of Mathematics and Statistics, University of Regina, Regina, S4S 0A2 Saskatchewan, Canada |
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Abstract: | The problem of simultaneous asymptotic estimation of eigenvalues of covariance matrix of Wishart matrix is considered under
a weighted quadratic loss function. James-Stein type of estimators are obtained which dominate the sample eigenvalues. The
relative merits of the proposed estimators are compared to the sample eigenvalues using asymptotic quadratic distributional
risk under loal alternatives. It is shown that the proposed estimators are asymptotically superior to the sample eigenvalues.
Further, it is demonstrated that the James-Stein type estimator is dominated by its truncated part. |
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Keywords: | Wishart distribution eigenvalues covariance matrix James-Stein type estimators positive-part estimators asymptotic quadratic bias and risk |
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