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:
|
672
|
Type:
|
Contributed
|
Date/Time:
|
Thursday, August 2, 2012 : 10:30 AM to 12:20 PM
|
Sponsor:
|
Section on Statistical Learning and Data Mining
|
Abstract - #305541 |
Title:
|
A More Powerful Two-Sample Test in High Dimensions Using Random Projection
|
Author(s):
|
Miles Lopes*+ and Laurent Jacob and Martin J. Wainwright
|
Companies:
|
University of California at Berkeley and University of California at Berkeley and University of California at Berkeley
|
Address:
|
1717 Euclid Ave, Apt. #12, Berkeley, CA, 94709, United States
|
Keywords:
|
high-dimensional statistics ;
hypothesis testing ;
two-sample test ;
random projection ;
gene set testing ;
dimension reduction
|
Abstract:
|
We study the hypothesis testing problem of detecting a shift between the means of two multivariate normal distributions in the high-dimensional setting, allowing for the data dimension p to exceed the sample size n. Specifically, we propose a new test statistic for the two-sample test of means that integrates a random projection with the classical Hotelling T^2 statistic. Working under a high-dimensional framework with (p,n) tending to infinity, we first derive an asymptotic power function for our test, and then provide sufficient conditions for it to achieve greater power than other state-of-the-art tests. Lastly, using ROC curves generated from simulated data, we demonstrate superior performance with competing tests in the parameter regimes anticipated by our theoretical results.
|
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.