This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.
Abstract Details
Activity Number:
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36
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Type:
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Contributed
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Date/Time:
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Sunday, August 1, 2010 : 2:00 PM to 3:50 PM
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Sponsor:
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Section on Nonparametric Statistics
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Abstract - #307218 |
Title:
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Simplex Techniques for Quantile Regression Model Selection
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Author(s):
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Yonggang Yao*+
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Companies:
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SAS Institute
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Address:
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100 SAS Campus Drive, Cary, NC, 27513,
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Keywords:
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Quantile Regression ;
Model Selection ;
Simplex Algorithm ;
Cross Validation ;
Greedy Algorithm ;
Statistical Regularization
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Abstract:
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It is well known that a regular quantile regression problem can be cast as a linear programming problem and be solved by using a Simplex algorithm. However, fast Simplex algorithms for quantile model selection have not been sufficiently explored in literature. This work discusses the Simplex-based techniques that achieve fast computation for quantile model selection. The focus is on how to manipulate a Simplex algorithm for a variety of model selection processes such as greedy algorithms (forward, backward, and stepwise selection methods), leave-one-out cross validation, and penalty methods (e.g., LASSO penalty).
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The address information is for the authors that have a + after their name.
Authors who are presenting talks have a * after their name.
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