Abstract Details
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Activity Number:
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332
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Type:
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Contributed
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Date/Time:
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Tuesday, August 5, 2014 : 10:30 AM to 12:20 PM
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Sponsor:
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IMS
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Abstract #312268
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Title:
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Two-Sample Thresholding Test for High-Dimensional Covariance Matrix
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Author(s):
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Bin Guo*+ and Song Xi Chen and Jun Li
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Companies:
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Peking University and Iowa State University/Peking University and Kent State University
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Keywords:
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High dimensional covariance ;
thresholding ;
large deviation
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Abstract:
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We propose a thresholding test for the equality of covariance matrices between two high dimensional populations. The test can achieve a power improvement by reducing the variance of the test statistics without thresholding. The asymptotic distribution of the test statistic is established and the corresponding power function is derived. Some simulation studies are carried out to confirm the theoretical results.
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Authors who are presenting talks have a * after their name.
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