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