The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.
Abstract Details
|
Activity Number:
|
586
|
|
Type:
|
Contributed
|
|
Date/Time:
|
Wednesday, August 3, 2011 : 2:00 PM to 3:50 PM
|
|
Sponsor:
|
Section on Statistics and Marketing
|
| Abstract - #301641 |
|
Title:
|
Order Detection for Factor Analysis Model Using Adaptive Group LASSO
|
|
Author(s):
|
Liuxia Wang*+ and Yulin Li
|
|
Companies:
|
Sentrana Inc. and K&L Consulting Services Inc
|
|
Address:
|
1725 I St. NW, Washington, DC, 20006,
|
|
Keywords:
|
Adaptive group lasso ;
selection consistency ;
factor analysis model ;
ECM algorithm
|
|
Abstract:
|
One crucial issue in factor analysis (FA) model is to detect the number of factors to summarize the original data. A wealth of approaches have been proposed for this matter. In this paper, we formulate the order detection for FA model into grouped variables selection in a regression, and the adaptive group lasso method is adopted for grouped variable selection. We show theoretically that the new method is able to identify the true number of factors consistently. We also illustrate this model using real and simulated examples. The simulations demonstrate that our approach outperforms some existing methods in terms of the percentage of correct order being detected.
|
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 2011 program
|
2011 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.