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Activity Number:
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165
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Type:
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Topic Contributed
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Date/Time:
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Monday, August 1, 2016 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Statistics in Epidemiology
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Abstract #320981
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Title:
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Identifying Interactions Using Convex Optimization
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Author(s):
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Jacob Bien* and Robert Tibshirani and Noah Simon
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Companies:
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Cornell University and Stanford University and University of Washington
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Keywords:
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interactions ;
sparsity ;
high-dimensional ;
convexity
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Abstract:
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We consider the testing of all pairwise interactions in a two-class problem with many features. We devise a hierarchical testing framework that considers an interaction only when one or more of its constituent features has a nonzero main effect. The test is based on a convex optimization framework that seamlessly considers main effects and interactions together. We show---both in simulation and on a genomic data set from the SAPPHIRe study---a potential gain in power and interpretability over a standard (nonhierarchical) interaction test.
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Authors who are presenting talks have a * after their name.
