This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.
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 2, 2010 : 8:30 AM to 10:20 AM
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Sponsor:
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Section on Statistical Computing
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Abstract - #306992 |
Title:
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Sparse Multivariate Regression with Covariance Estimation
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Author(s):
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Adam Rothman*+ and Elizaveta Levina and Ji Zhu
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Companies:
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University of Michigan and University of Michigan and University of Michigan
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Address:
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, , ,
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Keywords:
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Sparsity ;
multiple output regression ;
large p small n
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Abstract:
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We propose a procedure for constructing a sparse estimator of a multivariate regression coefficient matrix that accounts for correlation of the response variables. This method, which we call multivariate regression with covariance estimation (MRCE), involves penalized likelihood with simultaneous estimation of the regression coefficients and the covariance structure. An efficient optimization algorithm and a fast approximation are developed for computing MRCE. Using simulation studies, we show that the proposed method outperforms relevant competitors when the responses are highly correlated. We also apply the new method to a finance example on predicting asset returns.
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