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  Consistent Nonparametric Tests of Independence

Gretton, A., & Györfi, L.(2009). Consistent Nonparametric Tests of Independence (172). Tübingen, Germany: Max Planck Institute for Biological Cybernetics.

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MPIK-TR-172.pdf (Publisher version), 451KB
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Gretton, A1, 2, Author           
Györfi, L, Author
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1Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497795              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497794              

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 Abstract: Three simple and explicit procedures for testing the independence of two multi-dimensional random
variables are described. Two of the associated test statistics (L1, log-likelihood) are defined when the empirical
distribution of the variables is restricted to finite partitions. A third test statistic is defined as a kernel-based
independence measure. Two kinds of tests are provided. Distribution-free strong consistent tests are derived on the
basis of large deviation bounds on the test statistcs: these tests make almost surely no Type I or Type II error after
a random sample size. Asymptotically alpha-level tests are obtained from the limiting distribution of the test statistics.
For the latter tests, the Type I error converges to a fixed non-zero value alpha, and the Type II error drops to zero, for
increasing sample size. All tests reject the null hypothesis of independence if the test statistics become large. The
performance of the tests is evaluated experimentally on benchmark data.

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 Dates: 2009-07
 Publication Status: Issued
 Pages: 35
 Publishing info: Tübingen, Germany : Max Planck Institute for Biological Cybernetics
 Table of Contents: -
 Rev. Type: -
 Identifiers: Report Nr.: 172
BibTex Citekey: 6045
 Degree: -

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Title: Technical Report of the Max Planck Institute for Biological Cybernetics
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Pages: - Volume / Issue: 172 Sequence Number: - Start / End Page: - Identifier: -