Abstract Details
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Activity Number:
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27
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Type:
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Contributed
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Date/Time:
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Sunday, August 3, 2014 : 2:00 PM to 3:50 PM
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Sponsor:
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SSC
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Abstract #312741
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View Presentation
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Title:
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Testing High-Dimensional Covariance Matrices
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Author(s):
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Yingli Qin*+ and Weiming Li
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Companies:
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University of Waterloo and Beijing University of Posts and Telecommunications
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Keywords:
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High-dimension ;
covariance matrix ;
Stieltjes transform ;
Spectral distribution ;
asymptotic
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Abstract:
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We propose test statistics built upon the Stieltjes transform of the spectral distribution of the sample covariance matrices. We prove that the proposed statistics are asymptotically chi-square distributed under the null hypotheses, and normally distributed under the alternative hypotheses. Simulation results show that for finite dimension and sample size the proposed tests outperform some existing methods in various cases.
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Authors who are presenting talks have a * after their name.
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