2010/02/28 by Daniel Percival, Kathryn Roeder, Roni Rosenfeld +1
Biochemistry, Genetics and Molecular Biology · Immunology and Microbiology · Mathematics · #HIV Research and Treatment #HIV drug resistance #Human immunodeficiency virus (HIV) #Interpretability #Linear regression #Machine Learning in Bioinformatics #Measure (data warehouse) #Regression #Regression analysis #Statistical Methods and Inference #Stepwise regression #stat.AP #stat.ME
paper · pdf · doi:10.1214/10-aoas428
published as Annals of Applied Statistics 2011, Vol. 5, No. 2A, 628-644 · Published in at http://dx.doi.org/10.1214/10-AOAS428 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org)
openalex publication_date 2011/06/01 · arxiv created 2011/08/01 · arxiv updated 2011/08/02 · openalex created_date 2016/06/24 · openalex updated_date 2026/08/06
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 connection.