The Annals of Applied Statistics

Convex hierarchical testing of interactions

Jacob Bien, Noah Simon, and Robert Tibshirani

Full-text: Open access

Abstract

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.

Article information

Source
Ann. Appl. Stat., Volume 9, Number 1 (2015), 27-42.

Dates
First available in Project Euclid: 28 April 2015

Permanent link to this document
https://projecteuclid.org/euclid.aoas/1430226083

Digital Object Identifier
doi:10.1214/14-AOAS758

Mathematical Reviews number (MathSciNet)
MR3341106

Zentralblatt MATH identifier
06446559

Keywords
Interactions testing lasso

Citation

Bien, Jacob; Simon, Noah; Tibshirani, Robert. Convex hierarchical testing of interactions. Ann. Appl. Stat. 9 (2015), no. 1, 27--42. doi:10.1214/14-AOAS758. https://projecteuclid.org/euclid.aoas/1430226083


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References

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