Abstract Details
Activity Number:
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640
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Type:
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Topic Contributed
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Date/Time:
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Thursday, August 7, 2014 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Statistical Computing
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Abstract #312265
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View Presentation
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Title:
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Introducing a High-Performance SAS Procedure for Quantile Regression
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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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Keywords:
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quantile regression ;
High Performance Computing
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Abstract:
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Quantile regression is a systematic statistical methodology for modeling conditional quantile functions of a response variable on explanatory covariate effects. Unlike linear regression or poisson regression, which exclusively focuses on the conditional mean, quantile regression is distribution-free and can anatomize the entire response distribution and examine how the covariate effects influence the shape of the response distribution over the entire range of quantile levels ?[0,1]?. This presentation introduces a new high performance SAS procedure for quantile regression: HPQUANTSELECT, which runs in both single-machine and distributed-computing environment.
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Authors who are presenting talks have a * after their name.
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