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In this paper we explore the behaviour of dependent test statistics for testing of multiple hypothesis . To keep simplicity, we have considered a mixture normal model with equicorrelated correlation set up. With a simple linear…

Statistics Theory · Mathematics 2020-01-09 Rahul Roy , Subir Kumar Bhandari

We prove that an $m$ out of $n$ bootstrap procedure for Chatterjee's rank correlation is consistent whenever asymptotic normality of Chatterjee's rank correlation can be established. In particular, we prove that $m$ out of $n$ bootstrap…

Statistics Theory · Mathematics 2024-08-29 Holger Dette , Marius Kroll

(To appear in The American Statistician.) Distance covariance (Sz\'ekely, Rizzo, and Bakirov, 2007) is a fascinating recent notion, which is popular as a test for dependence of any type between random variables $X$ and $Y$. This approach…

Methodology · Statistics 2024-07-08 Jakob Raymaekers , Peter J. Rousseeuw

The Pearson product-moment correlation coefficient (rp) and the Spearman rank correlation coefficient (rs) are widely used in psychological research. We compare rp and rs on 3 criteria: variability, bias with respect to the population…

Methodology · Statistics 2024-08-29 J. C. F. de Winter , S. D. Gosling , J. Potter

Distance covariance is a popular measure of dependence between random variables. It has some robustness properties, but not all. We prove that the influence function of the usual distance covariance is bounded, but that its breakdown value…

Methodology · Statistics 2025-08-26 Sarah Leyder , Jakob Raymaekers , Peter J. Rousseeuw

Multivariate correlation analysis plays an important role in various fields such as statistics, economics, and big data analytics. In this paper, we propose a pair of measures, the unsigned correlation coefficient (UCC) and the unsigned…

Statistics Theory · Mathematics 2020-01-28 Jianji Wang , Nanning Zheng

The conditional randomization test (CRT) was recently proposed to test whether two random variables X and Y are conditionally independent given random variables Z. The CRT assumes that the conditional distribution of X given Z is known…

Machine Learning · Computer Science 2023-04-11 Shuai Li , Ziqi Chen , Hongtu Zhu , Christina Dan Wang , Wang Wen

Non-parametric correlation coefficients have been widely used for analysing arbitrary random variables upon common populations, when requiring an explicit error distribution to be known is an unacceptable assumption. We examine an…

Methodology · Statistics 2026-01-01 Landon Hurley

We propose a new bivariate symmetric copula with positive and negative dependence properties. The main features of the proposed copula are its simple mathematical structure, wider dependence range compared to FGM copula and its…

Statistics Theory · Mathematics 2024-08-29 Swaroop Georgy Zachariah , Mohd. Arshad , Ashok Kumar Pathak

We propose a nonparametric procedure to test for changes in correlation matrices at an unknown point in time. The new test requires only mild assumptions on the serial dependence structure and has considerable power in finite samples. We…

Methodology · Statistics 2014-10-29 Dominik Wied

We study an independence test based on distance correlation for random fields $(X,Y)$. We consider the situations when $(X,Y)$ is observed on a lattice with equidistant grid sizes and when $(X,Y)$ is observed at random locations. We provide…

Statistics Theory · Mathematics 2022-05-05 Muneya Matsui , Thomas Mikosch , Rasool Roozegar , Laleh Tafakori

Recent research in statistics has focused on dependence measures kappa(Y,X) taking values in [0, 1], where 0 characterizes independence of X and Y, and 1 perfect functional dependence of Y on X. One class of such measures consists of the…

Statistics Theory · Mathematics 2026-04-14 Jonathan Ansari

Measuring the (causal) direction and strength of dependence between two variables (events), Xi and Xj , is fundamental for all science. Our survey of decades-long literature on statistical dependence reveals that most assume symmetry in the…

Methodology · Statistics 2022-12-01 Hrishikesh Vinod

In this paper we develop a new tool for the comparison of paired data based on a new criterion of stochastic dominance that takes into account the dependence structure of the random variables under comparison. This new procedure provides a…

Statistics Theory · Mathematics 2026-01-27 F. Belzunce , C. Martínez-Riquelme

In this article we prove a generalization of the Ejsmont characterization of the multivariate normal distribution. Based on it, we propose a new test for independence and normality. The test uses an integral of the squared modulus of the…

Statistics Theory · Mathematics 2023-05-30 Wiktor Ejsmont , Bojana Milošević , Marko Obradović

The maximum correlation of functions of a pair of random variables is an important measure of stochastic dependence. It is known that this maximum nonlinear correlation is identical to the absolute value of the Pearson correlation for a…

Statistics Theory · Mathematics 2020-08-11 Zijian Guo , Cun-Hui Zhang

We give conditions under which a scalar random variable T can be coupled to a random scaling factor $\xi$ such that T and $\xi$T are rendered stochastically independent. A similar result is obtained for random measures. One consequence is a…

Probability · Mathematics 2017-03-08 Lancelot F. James , Peter Orbanz

In this article, we consider the problem of simultaneous testing of hypotheses when the individual test statistics are not necessarily independent. Specifically, we consider the problem of simultaneous testing of point null hypotheses…

Statistics Theory · Mathematics 2018-07-17 Prasenjit Ghosh , Arijit Chakrabarti

We explore how the classical concordance measures - Kendall's $\tau$, Spearman's rank correlation $\rho$, and Spearman's footrule $\phi$ - relate to Chatterjee's rank correlation $\xi$ when restricted to lower semilinear copulas. First, we…

Methodology · Statistics 2025-08-01 Sebastian Fuchs , Carsten Limbach , Fabian Schürrer

Mixing patterns in large self-organizing networks, such as the Internet, the World Wide Web, social and biological networks are often characterized by degree-degree {dependencies} between neighbouring nodes. One of the problems with the…

Probability · Mathematics 2014-02-03 Nelly Litvak , Remco van der Hofstad
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