Abstract Details
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Activity Number:
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161
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Type:
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Topic Contributed
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Date/Time:
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Monday, August 5, 2013 : 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 - #307986 |
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Title:
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Measuring and Testing Mutual Multivariate Independence
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Author(s):
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David Matteson*+
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Companies:
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Cornell University
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Keywords:
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Distance covariance ;
Nonparametric statistics ;
Permutation tests ;
U-statistics
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Abstract:
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We define several measures of mutual multivariate independence for random vectors of arbitrary and not necessarily equal dimensions. These non-negative measures are zero if and only if the random vectors are mutually independent. We define empirical dependence measures based on U-statistics of certain Euclidean distances between sample elements. Asymptotic properties are derived and we discuss testing for mutual multivariate independence. Implementation of the tests is demonstrated using real data examples and simulation results are presented.
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Authors who are presenting talks have a * after their name.
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