The exact equivalence of distance and kernel methods in hypothesis testing

DOI10.1007/s10182-020-00378-1zbMath1480.62079arXiv1806.05514OpenAlexW3089526752MaRDI QIDQ2058548

Joshua T. Vogelstein, Cencheng Shen

Publication date: 9 December 2021

Published in: AStA. Advances in Statistical Analysis (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1806.05514

zbMATH Keywords

distance covarianceHilbert-Schmidt independence criterioncharacteristic kernelstrong negative-type metric

Mathematics Subject Classification ID

Nonparametric hypothesis testing (62G10) Measures of association (correlation, canonical correlation, etc.) (62H20)

Related Items (5)

The Chi-Square Test of Distance Correlation ⋮ EuMMD: efficiently computing the MMD two-sample test statistic for univariate data ⋮ A nonparametric test for comparing survival functions based on restricted distance correlation ⋮ Test of conditional independence in factor models via Hilbert-Schmidt independence criterion ⋮ A regression perspective on generalized distance covariance and the Hilbert-Schmidt independence criterion

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