Abstract Details
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 - #307899 |
Title:
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A Fiducial Approach to Sparse Covariance Estimation
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Author(s):
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Wen Shi*+ and Jan Hannig
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Companies:
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UNC and UNC-Chapel Hill
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Keywords:
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Covariance estimation ;
sparse ;
fiducial inference ;
reversible jump Markov chain ;
high dimension low sample size
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Abstract:
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We propose a sparse covariance estimation method for over-parametrized models via fiducial distribution of the covariate matrix with minimum description length penalty. Incorporating a reversible jump Markov chain Monte Carlo procedure, our fiducial distribution based approach efficiently produces a plausible covariance estimator as well as a confidence interval. The algorithm generates comparable results to existing methods with appropriate sparsity assumptions under the framework of high dimension low sample size.
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Authors who are presenting talks have a * after their name.
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