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Selecting the Best Component of a Multivariate Normal Population

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  • Yoshikazu Takada

Abstract

This article considers the problem of selecting the best component of a mean vector of a multivariate normal distribution. Using Bechhofer's indifference-zone approach, Clark and Yang (1986) proposed a two-stage selection procedure to solve the problem when the covariance matrix is totally unknown. We are interested in the asymptotic performances of their sample size and show that their procedure becomes asymptotically first-order efficient, but is not asymptotically second-order efficient. We propose a three-stage procedure which enjoys an asymptotically second-order efficiency.

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  • Yoshikazu Takada, 2009. "Selecting the Best Component of a Multivariate Normal Population," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 38(16-17), pages 3198-3212, October.
    • Handle: RePEc:taf:lstaxx:v:38:y:2009:i:16-17:p:3198-3212
    DOI: 10.1080/03610920902947733
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