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: 307
Type: Invited
Date/Time: Tuesday, July 31, 2012 : 10:30 AM to 12:20 PM
Sponsor: JCGS-Journal of Computational and Graphical Statistics
Abstract - #303475
Title: Functional Robust Support Vector Machines for Sparse and Irregular Longitudinal Data
Author(s): Yichao Wu*+ and Yufeng Liu
Companies: North Carolina State University and The University of North Carolina at Chapel Hill
Address: Department of Statistics, Raleigh, NC, , USA
Keywords: classification ; functional principal component analysis ; longitudinal data ; multicategory ; sparse and irregular ; truncated-hinge-loss SVM

This paper focuses on sparse and irregular longitudinal data with a multicategory response. The predictor consists of sparse and irregular observations, potentially contaminated with measurement errors, on the predictor trajectory. To deal with this type of complicated predictors, we borrow the strength of large margin classifiers in statistical learning for classification of sparse and irregular longitudinal data. In particular, we propose functional robust truncated-hinge-loss support vector machines to perform multicategory classification with the aid of functional principal component analysis.

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.