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arXiv · 1002.3128

Structured, sparse regression with application to HIV drug resistance

Daniel Percival·Kathryn Roeder·Roni Rosenfeld·Larry Wasserman
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Abstract

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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Daniel Percival, Kathryn Roeder, Roni Rosenfeld, Larry Wasserman. 2010-02-16. Structured, sparse regression with application to HIV drug resistance. https://doi.org/10.1214/10-aoas428

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