TY - JOUR
T1 - Distribution-free tests of multivariate independence based on center-outward quadrant, Spearman, Kendall, and van der Waerden statistics
AU - Shi, Hongjian
AU - Drton, Mathias
AU - Hallin, Marc
AU - Han, Fang
N1 - Publisher Copyright:
© 2025 ISI/BS.
PY - 2025/2
Y1 - 2025/2
N2 - Due to the lack of a canonical ordering in Rd for d > 1, defining multivariate generalizations of the classical univariate ranks has been a long-standing open problem in statistics. Optimal transport has been shown to offer a solution in which multivariate ranks are obtained by transporting data points to a grid that approximates a uniform reference measure (Ann. Statist. 45 (2017) 223–256; Hallin (2017); Ann. Statist. 49 (2021) 1139–1165), thereby inducing ranks, signs, and a data-driven ordering of Rd. We take up this new perspective to define and study multivariate analogues of the sign covariance/quadrant statistic, Spearman’s rho, Kendall’s tau, and van der Waerden covariances. The resulting tests of multivariate independence are fully distribution-free, hence uniformly valid irrespective of the actual (absolutely continuous) distribution of the observations. Our results provide the asymptotic distribution theory for these new test statistics, with asymptotic approximations to critical values to be used for testing independence between random vectors, as well as a power analysis of the resulting tests in an extension of the so-called (bivariate) Konijn model. This power analysis includes a multivariate Chernoff–Savage property guaranteeing that, under elliptical generalized Konijn models, the asymptotic relative efficiency of our van der Waerden tests with respect to Wilks’ classical (pseudo-)Gaussian procedure is strictly larger than or equal to one, where equality is achieved under Gaussian distributions only. We similarly provide a lower bound for the asymptotic relative efficiency of our Spearman procedure with respect to Wilks’ test, thus extending the classical result by Hodges and Lehmann on the asymptotic relative efficiency, in univariate location models, of Wilcoxon tests with respect to the Student ones.
AB - Due to the lack of a canonical ordering in Rd for d > 1, defining multivariate generalizations of the classical univariate ranks has been a long-standing open problem in statistics. Optimal transport has been shown to offer a solution in which multivariate ranks are obtained by transporting data points to a grid that approximates a uniform reference measure (Ann. Statist. 45 (2017) 223–256; Hallin (2017); Ann. Statist. 49 (2021) 1139–1165), thereby inducing ranks, signs, and a data-driven ordering of Rd. We take up this new perspective to define and study multivariate analogues of the sign covariance/quadrant statistic, Spearman’s rho, Kendall’s tau, and van der Waerden covariances. The resulting tests of multivariate independence are fully distribution-free, hence uniformly valid irrespective of the actual (absolutely continuous) distribution of the observations. Our results provide the asymptotic distribution theory for these new test statistics, with asymptotic approximations to critical values to be used for testing independence between random vectors, as well as a power analysis of the resulting tests in an extension of the so-called (bivariate) Konijn model. This power analysis includes a multivariate Chernoff–Savage property guaranteeing that, under elliptical generalized Konijn models, the asymptotic relative efficiency of our van der Waerden tests with respect to Wilks’ classical (pseudo-)Gaussian procedure is strictly larger than or equal to one, where equality is achieved under Gaussian distributions only. We similarly provide a lower bound for the asymptotic relative efficiency of our Spearman procedure with respect to Wilks’ test, thus extending the classical result by Hodges and Lehmann on the asymptotic relative efficiency, in univariate location models, of Wilcoxon tests with respect to the Student ones.
KW - Center-outward ranks and signs
KW - elliptical Chernoff–Savage property
KW - multivariate independence test
KW - Pitman asymptotic relative efficiency
UR - http://www.scopus.com/inward/record.url?scp=85208636159&partnerID=8YFLogxK
U2 - 10.3150/24-BEJ1721
DO - 10.3150/24-BEJ1721
M3 - Article
AN - SCOPUS:85208636159
SN - 1350-7265
VL - 31
SP - 106
EP - 129
JO - Bernoulli
JF - Bernoulli
IS - 1
ER -