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:
|
296
|
|
Type:
|
Contributed
|
|
Date/Time:
|
Tuesday, July 31, 2012 : 8:30 AM to 10:20 AM
|
|
Sponsor:
|
Biometrics Section
|
| Abstract - #306776 |
|
Title:
|
Hypothesis Testing in High-Dimensional Sparse Regression
|
|
Author(s):
|
Rajarshi Mukherjee*+
|
|
Companies:
|
|
|
Address:
|
56 Calumet Street, Boston, MA, 02120, United States
|
|
Keywords:
|
Hypothesis Testing ;
High Dimensional Sparse Regression ;
Relative Efficiency of Tests
|
|
Abstract:
|
We study the problem of hypothesis testing in high dimensional sparse regression. We study the properties of a class of tests introduced for this purpose. The results are derived in a high dimensional regression setting with p variables and we suppose that under the alternative only k of them are non-zero where k is much smaller than p.We identify different classes of alternatives under which the proposed classes of tests can be classified to have differential behavior of power functions.The results are non asymptotic in nature as we provide finite sample bounds on the testing errors. As a result we also derive the relative efficiencies of the tests with respect to the classical tests in the high dimensional sparse regression setting.
|
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.