Kernel-based method for joint independence of functional variables

Terence Kevin Manfoumbi Djonguet and Guy Martial Nkiet

Communications in Statistics - Theory and Methods, 2025, vol. 54, issue 3, 921-937

Abstract: This work investigates the problem of testing whether d functional random variables are jointly independent, using a modified estimator of the d-variable Hilbert Schmidt Indepedence Criterion (dHSIC). We then get the asymptotic normality of this estimator both under the joint independence hypothesis and under the alternative hypothesis. A simulation study shows the good performance of the proposed test on a finite sample.

Date: 2025
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DOI: 10.1080/03610926.2024.2326545

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