Strongly consistent nonparametric tests of conditional independence
A simple and explicit procedure for testing the conditional independence of two multi-dimensional random variables given a third random vector is described. The associated L1-based test statistic is defined for when the empirical distribution of the variables is restricted to finite partitions. Distribution-free strong consistency is proved.
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Volume (Year): 82 (2012)
Issue (Month): 6 ()
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- Oliver Linton & Pedro Gozalo, 1996. "Conditional Independence Restrictions: Testing and Estimation," Cowles Foundation Discussion Papers 1140, Cowles Foundation for Research in Economics, Yale University.
- Beran, R. & Bilodeau, M. & Lafaye de Micheaux, P., 2007. "Nonparametric tests of independence between random vectors," Journal of Multivariate Analysis, Elsevier, vol. 98(9), pages 1805-1824, October.
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- Csörgo, Sándor, 1985. "Testing for independence by the empirical characteristic function," Journal of Multivariate Analysis, Elsevier, vol. 16(3), pages 290-299, June.
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