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Abstract Details
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Activity Number:
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63
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Type:
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Topic Contributed
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Date/Time:
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Sunday, July 29, 2012 : 4:00 PM to 5:50 AM
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Sponsor:
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ENAR
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| Abstract - #304241 |
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Title:
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Empirical Likelihood Method for a High-Dimensional Covariance Matrix
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Author(s):
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Liang Peng*+
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Companies:
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Georgia Institute of Technology
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Address:
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School of Mathematics, Atlanta, GA, 30332-0160, United States
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Keywords:
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Empirical Likelihood ;
High dimension ;
covariance matrix
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Abstract:
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It is of interest to test some special structure of a high dimensional covariance matrix such as banded structure. We propose a novel empirical likelihood method which works for both fixed and divergent dimension. The asymptotic limit of the new test is always a chi-square distribution so that no ad hoc approach is needed to obtain critical points.
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Authors who are presenting talks have a * after their name.
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