Interpoint-ranking sign covariance for the test of independence

Prediction by supervised principal components

Haeun Moon and Kehui Chen

Biometrika, 2022, vol. 109, issue 1, 165-179

Abstract: SummaryWe generalize the sign covariance introduced by Bergsma & Dassios (2014) to multivariate random variables and beyond. The new interpoint-ranking sign covariance is applicable to general types of random objects as long as a meaningful similarity measure can be defined, and it is shown to be zero if and only if the two random variables are independent. The test statistic is a -statistic, whose large-sample behaviour guarantees that the proposed test is consistent against general types of alternatives. Numerical experiments and data analyses demonstrate the superior empirical performance of the proposed method.

Keywords: Consistency; Independence test; Interpoint distance; Nonparametric test; Sign covariance (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (1)

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