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Article Dans Une Revue Journal of Multivariate Analysis Année : 2022

Conditional independence testing via weighted partial copulas and nearest neighbors

Résumé

This paper introduces the \textit{weighted partial copula} function for testing conditional independence. The proposed test procedure results from these two ingredients: (i) the test statistic is an explicit Cramer-von Mises transformation of the \textit{weighted partial copula}, (ii) the regions of rejection are computed using a bootstrap procedure which mimics conditional independence by generating samples from the product measure of the estimated conditional marginals. Under conditional independence, the weak convergence of the \textit{weighted partial copula proces}s is established when the marginals are estimated using a smoothed local linear estimator. Finally, an experimental section demonstrates that the proposed test has competitive power compared to recent state-of-the-art methods such as kernel-based test.

Dates et versions

hal-04276085 , version 1 (08-11-2023)

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Citer

Pascal Bianchi, Kevin Elgui, François Portier. Conditional independence testing via weighted partial copulas and nearest neighbors. Journal of Multivariate Analysis, 2022, 30 (3), pp.1117-1147. ⟨hal-04276085⟩
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