Effective dimension reduction for sparse functional data.

TitleEffective dimension reduction for sparse functional data.
Publication TypeJournal Article
Year of Publication2015
AuthorsYao, F, E Lei, and Y Wu
JournalBiometrika
Volume102
Issue2
Pagination421-437
Date Published2015 Jun
ISSN0006-3444
Abstract

We propose a method of effective dimension reduction for functional data, emphasizing the sparse design where one observes only a few noisy and irregular measurements for some or all of the subjects. The proposed method borrows strength across the entire sample and provides a way to characterize the effective dimension reduction space, via functional cumulative slicing. Our theoretical study reveals a bias-variance trade-off associated with the regularizing truncation and decaying structures of the predictor process and the effective dimension reduction space. A simulation study and an application illustrate the superior finite-sample performance of the method.

DOI10.1093/biomet/asv006
Alternate JournalBiometrika
Original PublicationEffective dimension reduction for sparse functional data.
PubMed ID26566293
PubMed Central IDPMC4640368
Grant ListP01 CA142538 / CA / NCI NIH HHS / United States
R01 CA149569 / CA / NCI NIH HHS / United States