Abstract Details
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Activity Number:
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136
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Type:
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Contributed
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Date/Time:
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Monday, August 5, 2013 : 8:30 AM to 10:20 AM
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Sponsor:
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IMS
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| Abstract - #309016 |
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Title:
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Thresholding Test for Bandedness of Covariance Matrices
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Author(s):
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Jing He*+ and Song Xi Chen
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Companies:
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Peking University and Peking University and Iowa State University
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Keywords:
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high dimension ;
thresholding ;
bandedness ;
sparse covariance matrix
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Abstract:
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We propose a thresholding test for the bandedness of high dimensional covariance matrices, which is designed to maintain a good level of power when the underlying covariance is sparse. The thresholding is conducted on the subdiagonals, after establishing the asymptotic properties of the subdiagonals. This test is nonparametric and can accommodate the "large p, small n" situations without an explicit relationship between the sample size n and the dimension p. It has been shown that the new test is powerful in detecting sparse signals in the covariance. The properties of the test are demonstrated by both theoretical and simulation studies.
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Authors who are presenting talks have a * after their name.
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