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:
|
114
|
|
Type:
|
Topic Contributed
|
|
Date/Time:
|
Monday, July 30, 2012 : 8:30 AM to 10:20 AM
|
|
Sponsor:
|
Section on Statistical Computing
|
| Abstract - #304801 |
|
Title:
|
Partially Linear Structure Identification in Generalized Additive Models with NP-Dimensionality
|
|
Author(s):
|
Pang Du*+ and Heng Lian and Hua Liang
|
|
Companies:
|
Virginia Tech and National University of Singapore and University of Rochester
|
|
Address:
|
410 Hutcheson Hall 0439, Blacksburg, VA, 24061, United States
|
|
Keywords:
|
Splines ;
Quasi-likelihood ;
SCAD penalty ;
Partially linear models ;
NP-dimensionality
|
|
Abstract:
|
Separation of the parametric and nonparametric components in additive models based on penalized likelihood has received attention recently. However, it remains unknown whether consistent separation is possible in generalized additive models, and how high dimensionality the method can handle. In this article, we study the doubly SCAD-penalized approach for problems of non-polynomial (NP) dimensionality and demonstrate its oracle property.
|
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.