This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.
Abstract Details
Activity Number:
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81
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Type:
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Contributed
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Date/Time:
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Sunday, August 1, 2010 : 4:00 PM to 5:50 PM
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Sponsor:
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Section on Statistical Learning and Data Mining
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Abstract - #307288 |
Title:
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Model Identification and Regression Estimation with a Diverging Number of Predictors
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Author(s):
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Zhan Wang*+ and Yuhong Yang
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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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1293 Fifield Place, Falcon Heights, MN, 55108,
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Keywords:
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Consistency ;
Minimax-rate optimality ;
Model selection ;
Invariance test ;
Lasso ;
SCAD
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Abstract:
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In model selection problems where the true model is fixed and the sample size increases, it is now well known that if a model selection criterion is consistent, it cannot be minimax-rate optimal for estimation. In some situations, more variables are introduced as the sample size increases and it may be more realistic to treat the true model as a changing target when information accumulates. In this case, we prove that a conflict between model selection consistency and minimax-rate optimality of estimation still exists as long as some mild conditions are satisfied. In particular, we show that all model selection methods that have a certain invariance property are subject to this conflict.
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Authors who are presenting talks have a * after their name.
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