This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.
Abstract Details
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Activity Number:
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297
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Type:
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Contributed
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Date/Time:
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Tuesday, August 3, 2010 : 8:30 AM to 10:20 AM
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Sponsor:
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Biometrics Section
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| Abstract - #306971 |
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Title:
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Partial Envelopes: A Focused Method for Efficient Estimation in Multivariate Linear Regression
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Author(s):
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Zhihua Su*+ and Ralph Dennis Cook
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Companies:
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University of Minnesota and University of Minnesota
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Address:
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224 Church Street SE, Minneapolis, MN, 55455, United States
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Keywords:
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envelope model ;
sufficient dimension reduction ;
multivariate analysis ;
maximum likelihood estimation
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Abstract:
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The partial envelope model is a parsimonious method for multivariate linear regression when some of the predictors are of special interest. It has the potential to achieve massive efficiency gains compared to the standard model in the estimation of the coefficients for the selected predictors, therefore can greatly reduce the sample size in a study. The partial envelope model is a variation on the envelope model, proposed by Cook, Li and Chiaromonte (2010) but, as it focuses on part of the predictors, it has looser restrictions and can further improve efficiency.
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