The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.
Online Program Home
Abstract Details
Activity Number:
|
375
|
Type:
|
Invited
|
Date/Time:
|
Tuesday, July 31, 2012 : 2:00 PM to 3:50 PM
|
Sponsor:
|
ENAR
|
Abstract - #303561 |
Title:
|
Semiparametric Functional Linear Model with High-Dimensional Covariates
|
Author(s):
|
Fang Yao*+ and Hao Helen Zhang and Dehan Kong
|
Companies:
|
University of Toronto and North Carolina State University and North Carolina State University
|
Address:
|
Department of Statistics, Toronto, ON, , Canada
|
Keywords:
|
Functional data analysis ;
Functional linear model ;
Model selection ;
Principal components ;
SCAD ;
Semiparametrics
|
Abstract:
|
We propose and study a new class of semiparametric functional regression models motivated by the complex nature of data encountered in modern scientific experiments. With a scalar response, multiple covariates are collected, a large number of which are time-independent and directly observed and a few may be functional with underlying processes. The goal is to jointly model the functional and non-functional predictors, identifying important scalar covariates while taking into account the functional covariate. In particular we exploit a unified linear structure to incorporate the functional predictor as in classical functional linear models that is of nonparametric feature. Simultaneously we include a potentially large number of scalar predictors as the parametric part that may be reduced to a sparse representation. Theoretical and empirical investigation reveals that the efficient estimation regarding important scalar predictors can be obtained and enjoys the oracle property, despite contamination of the noise-prone functional covariate.
|
The address information is for the authors that have a + after their name.
Authors who are presenting talks have a * after their name.
Back to the full JSM 2012 program
|
2012 JSM Online Program Home
For information, contact jsm@amstat.org or phone (888) 231-3473.
If you have questions about the Continuing Education program, please contact the Education Department.