JSM 2012 Home

JSM 2012 Online Program

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: 568
Type: Contributed
Date/Time: Wednesday, August 1, 2012 : 2:00 PM to 3:50 PM
Sponsor: Section on Statistical Learning and Data Mining
Abstract - #305511
Title: Groupwise Elastic Net
Author(s): Miae Oh*+ and Yongdai Kim
Companies: and Seoul National University
Address: College of Natural Sciences, Seoul Natio, Seoul, _, 151-742, South Korea
Keywords: Elastic net ; group variable selection ; high-dimensional data ; penalized regression

In this talk, we consider a problem of model selection and estimation in sparse, high-dimensional regression models where covariates are grouped. We propose a new regularization method which can reflected a correlation structure between groups. We propose a combination of doubly sparse and groupwise quadratic penalties where the former ensures groupwise sparsity and the later promotes simultaneous selection of highly correlated groups. The proposed method is applied to real examples.

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.