Kernel-based tests for joint independence

We investigate the problem of testing whether d possibly multivariate random variables, which may or may not be continuous, are jointly (or mutually) independent. Our method builds on ideas of the two-variable Hilbert–Schmidt independence criterion but allows for an arbitrary number of variables. We...

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Bibliographische Detailangaben

Veröffentlicht in:	Journal of the Royal Statistical Society. Series B, Statistical methodology Statistical methodology, 2018-01, Vol.80 (1), p.5-31
Hauptverfasser:	Pfister, Niklas, Bühlmann, Peter, Schölkopf, Bernhard, Peters, Jonas
Format:	Artikel
Sprache:	eng
Schlagworte:	Causal inference Criteria Discovery Hilbert space Independence test Independent variables Kernel methods Permutations Random variables Regression analysis Statistical methods Statistics Variables V‐statistics
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