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Computational Statistics & Data Analysis
Volume 52, Issue 5, 20 January 2008, Pages 2714-2724
 
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doi:10.1016/j.csda.2007.09.028    How to Cite or Link Using DOI (Opens New Window)
Copyright © 2007 Elsevier B.V. All rights reserved.

Large sample approximations for the LR statistic for equality of the smallest eigenvalues of a covariance matrix under elliptical population

Daisuke Watanabea, Susumu Okadaa, Yasunori FujikoshiCorresponding Author Contact Information, a, E-mail The Corresponding Author and Takakazu Sugiyamaa

aDepartment of Mathematics, Graduate School of Science and Engineering, Chuo University, 1-13-27 Kasuga, Bunkyo-ku, Tokyo 112-8551, Japan

Received 9 October 2006; 
revised 22 July 2007; 
accepted 26 September 2007. 
Available online 4 October 2007.

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Abstract

This paper is concerned with large sample approximations of the LR statistic for testing the hypothesis that the smallest eigenvalues of a covariance matrix are equal. Under a normal population Lawley [1956. Tests of significance for the latent roots of covariance and correlation matrices. Biometrika 43, 128–136.] and Fujikoshi [1977. An asymptotic expansion for the distributions of the latent roots of the Wishart matrix with multiple population roots. Ann. Inst. Statist. Math. 29, 379–387.] obtained a Bartlett-correction factor and an asymptotic expansion for the LR statistic, respectively, when the sample size is large. In this paper we extend the Bartlett correction factor to an elliptical population. The accuracy of our approximations is examined through simulation experiments.

Keywords: Bartlett correction; Elliptical distribution; Likelihood ratio statistic; Principal component analysis

Article Outline

1. Introduction
2. The distribution of LR statistic under an elliptical population
2.1. Preliminaries
2.2. The limiting distribution
2.3. Bartlett-correction factor
3. Simulation study
4. Conclusion
References

 
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