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Asymptotic Improvement of the Usual Confidence Set in a Multivariate Normal Distribution with Unknown Variance

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  • Takada, Yoshikazu

Abstract

We consider confidence sets for the mean of a multivariate normal distribution with unknown covariance matrix of the form[sigma]2I. The coverage probability of the usual confidence set is shown to be improved asymptotically by centering at a shrinkage estimator.

Suggested Citation

  • Takada, Yoshikazu, 1998. "Asymptotic Improvement of the Usual Confidence Set in a Multivariate Normal Distribution with Unknown Variance," Journal of Multivariate Analysis, Elsevier, vol. 64(2), pages 118-130, February.
  • Handle: RePEc:eee:jmvana:v:64:y:1998:i:2:p:118-130
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    References listed on IDEAS

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    1. Hwang, J. T. Gene & Ullah, Aman, 1994. "Confidence sets centered at James--Stein estimators : A surprise concerning the unknown-variance case," Journal of Econometrics, Elsevier, vol. 60(1-2), pages 145-156.
    2. Robert, Christian & Casella, George, 1990. "Improved confidence sets for spherically symmetric distributions," Journal of Multivariate Analysis, Elsevier, vol. 32(1), pages 84-94, January.
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