This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.

Abstract Details

Activity Number: 180
Type: Contributed
Date/Time: Monday, August 2, 2010 : 10:30 AM to 12:20 PM
Sponsor: Section on Nonparametric Statistics
Abstract - #308436
Title: Nonparametric Weighted Log-Rank Tests for Comparing Multivariate Distributions
Author(s): Xiaoru Wu*+ and Zhiliang Ying and Tian Zheng
Companies: Columbia University and Columbia University and Columbia University
Address: , , 10027,
Keywords: Gaussian random field ; High-dimensional ; Permutation test ; Random weighting ; Rank statistics ; Weak convergence
Abstract:

A flexible approach to testing equality of two or more populations is developed. It is based on the class of weighted log-rank statistics commonly used in survival analysis. The test statistics are nonparametric, computationally simple and applicable to high-dimensional data. We show that the underlying log-rank score process converges weakly to a Gaussian random field. To obtain the approximate cutoff points for the test statistics, a random weighting method is proposed and justified. The new approach is applied to a study of brain activation measured by functional magnetic resonance imaging during two linguistic tasks and a handwritten digit recognition data set.


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