The Annals of Applied Statistics

Structured, sparse regression with application to HIV drug resistance

Daniel Percival, Kathryn Roeder, Roni Rosenfeld, and Larry Wasserman

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We introduce a new version of forward stepwise regression. Our modification finds solutions to regression problems where the selected predictors appear in a structured pattern, with respect to a predefined distance measure over the candidate predictors. Our method is motivated by the problem of predicting HIV-1 drug resistance from protein sequences. We find that our method improves the interpretability of drug resistance while producing comparable predictive accuracy to standard methods. We also demonstrate our method in a simulation study and present some theoretical results and connections.

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Ann. Appl. Stat., Volume 5, Number 2A (2011), 628-644.

First available in Project Euclid: 13 July 2011

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Sparsity variable selection regression greedy algorithms


Percival, Daniel; Roeder, Kathryn; Rosenfeld, Roni; Wasserman, Larry. Structured, sparse regression with application to HIV drug resistance. Ann. Appl. Stat. 5 (2011), no. 2A, 628--644. doi:10.1214/10-AOAS428.

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