"Estimating the Covariance Matrix: A New Approach", June 1999

Tatsuya Kubokawa and M. S. Srivastava
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Tatsuya Kubokawa: Faculty of Economics, University of Tokyo
M. S. Srivastava: University of Toronto

No CIRJE-F-52, CIRJE F-Series from CIRJE, Faculty of Economics, University of Tokyo

Abstract: In this paper, we consider the problem of estimating the covaraince matrix and the generalized variance when the observations follow a nonsingular multivariate normal distribution with unknown mean. A new method is presented to obtain a truncated estimator that utilizes the information available in the sample mean matrix and dominates the James-Stein minimax estimator. Several scale equivariant minimax estimators are also given. This method is then applied to obtain new truncated and improved estimators of the generalized variance; it also provides a new proof to the results of Shorrock and Zidek (1976) and Sinha (1976).

Pages: 26 pages
Date: 1999-06
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Citations: View citations in EconPapers (2)

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