Automatic structure recovery for additive models.

TitleAutomatic structure recovery for additive models.
Publication TypeJournal Article
Year of Publication2015
AuthorsWu, Yichao, and Leonard A. Stefanski
Date Published2015 Jun 02

We propose an automatic structure recovery method for additive models, based on a backfitting algorithm coupled with local polynomial smoothing, in conjunction with a new kernel-based variable selection strategy. Our method produces estimates of the set of noise predictors, the sets of predictors that contribute polynomially at different degrees up to a specified degree , and the set of predictors that contribute beyond polynomially of degree . We prove consistency of the proposed method, and describe an extension to partially linear models. Finite-sample performance of the method is illustrated via Monte Carlo studies and a real-data example.

Alternate JournalBiometrika
Original PublicationAutomatic structure recovery for additive models.
PubMed ID26146407
PubMed Central IDPMC4487890
Grant ListP01 CA142538 / CA / NCI NIH HHS / United States
R01 CA149569 / CA / NCI NIH HHS / United States