JSM 2011 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.

Abstract Details

Activity Number: 152
Type: Invited
Date/Time: Monday, August 1, 2011 : 10:30 AM to 12:20 PM
Sponsor: Section on Nonparametric Statistics
Abstract - #300118
Title: Sparse Quantile Regression Approach for Analyzing Heterogeneity in Ultrahigh-Dimension
Author(s): Runze Li*+ and Lan Wang and Yichao Wu
Companies: Penn State University and University of Minnesota and North Carolina State University
Address: Department of Statistics, University Park, PA, 16802-2111,
Keywords: Quantile Regression ; SCAD ; Ultrahigh-dimensional data
Abstract:

Ultrahigh-dimensional data is often heterogeneous due to either heteroscedastic variance or other forms of non-location-shift covariate effects. Quantile regression is particularly useful for analyzing data from heterogeneous population. Usually in practice, only a few covariates influence the conditional distribution of the response variable given all candidate covariates. We propose to systematically study sparse quantile regression for ultrahigh-dimensional data. For both computation and theoretic development, it is challenging to deal with both the nonsmooth loss function and the nonconvex penalty function in ultrahigh-dimensional parameter space. We develop a new algorithm to deal with computational issue and theoretically analyze the proposed algorithm. The new algorithm enables us to establish a new formulation of the oracle property for ultrahigh-dimensional data. We further study the sampling properties of the penalized quantile regression for ultrahigh-dimensional data under some regularity conditions which are weaker and more reasonable conditions than the existing ones in the literature.


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.