Abstract Details
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Activity Number:
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322
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Type:
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Topic 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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IMS
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Abstract #312311
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View Presentation
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Title:
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Optimal Prior-Free Probabilistic Variable Selection in Regression
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Author(s):
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Ryan Martin*+
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Companies:
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Keywords:
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belief ;
inferential model ;
plausibility ;
random set ;
regression ;
variable selection
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Abstract:
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Variable selection in linear regression is a fundamental problem. In the inferential model (IM) framework, variable selection corresponds to simultaneous consideration of several complex assertions about the slope parameter vector. I will discuss the general construction of optimal predictive random sets for simultaneous assertions subject to a balance condition, and apply these ideas to the variable selection problem. Simulation results demonstrate the superior performance of the IM-based method compared to those based on lasso, AIC, etc.
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Authors who are presenting talks have a * after their name.
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