\(K\)-sample problem using strong approximations of empirical copula processes

DOI10.3103/S1066530711010029zbMath1282.62115MaRDI QIDQ2437992

T. Zari, Amor Keziou, Salim Bouzebda

Publication date: 10 March 2014

Published in: Mathematical Methods of Statistics (Search for Journal in Brave)

zbMATH Keywords

dependence functionGaussian processestest of independencestrong invariance principlesempirical copula processes\(K\)-sample problem

Mathematics Subject Classification ID

Nonparametric hypothesis testing (62G10) Asymptotic properties of nonparametric inference (62G20) Hypothesis testing in multivariate analysis (62H15) Order statistics; empirical distribution functions (62G30) Strong limit theorems (60F15)

Related Items (12)

Asymptotic behavior of weighted multivariate Cramér-von Mises-type statistics under contiguous alternatives ⋮ On the strong approximation of bootstrapped empirical copula processes with applications ⋮ Rank correlation under categorical confounding ⋮ About tests of the ``simplifying assumption for conditional copulas ⋮ Comparing a large number of multivariate distributions ⋮ Some new multivariate tests of independence ⋮ Strong approximation of multidimensional \(\mathbb P\)-\(\mathbb P\) plots processes by Gaussian processes with applications to statistical tests ⋮ K-Sample Test for Equality of Copulas ⋮ Strong approximations for the \(p\)-fold integrated empirical process with applications to statistical tests ⋮ Testing for equality between conditional copulas given discretized conditioning events ⋮ Some asymptotic results for the integrated empirical process with applications to statistical tests ⋮ Strong approximation of empirical copula processes by Gaussian processes

Uses Software

• TwoCop

Cites Work

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• A kolmogorov-smirnov type test for positive quadrant dependence

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