Abstract Details
Activity Number:
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350
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Type:
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Contributed
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Date/Time:
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Tuesday, August 5, 2014 : 10:30 AM to 12:20 PM
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Sponsor:
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Biopharmaceutical Section
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Abstract #312800
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Title:
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A Flexible and Super-Fast Quantile Regression Solver
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Author(s):
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Youlan Rao*+ and Yonggang Yao
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Companies:
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Parexel and SAS Institute
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Keywords:
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quantile regression ;
LASSO QR ;
elastic-net QR ;
simulation ;
real application
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Abstract:
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We present a unified algorithm framework for solving Quantile Regression(QR), LASSO QR, and elastic-net QR. This method smoothies check loss, LASSO and elastic-net penalty with their linear-quadratic approximation substitutes, so that these types of QR problems can be solved by using iterative least squares method. Because the solution of a QR problem only relies on a small support subset of all the observations, our algorithm could solve a QR problem faster than the ordinary-least-squares method for linear regression for a given data set. We demonstrate the performance of this new algorithm with a simulation study and a real patients' data analysis in a clinical trial.
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Authors who are presenting talks have a * after their name.
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