Large-Sample Theory for the Bergsma-Dassios Sign Covariance

DOI10.48550/arXiv.1602.04387zbMath1346.62094arXiv1602.04387WikidataQ57566379 ScholiaQ57566379MaRDI QIDQ146217

Mathias Drton, Luca Weihs, Preetam Nandy, Preetam Nandy

Publication date: 13 February 2016

Published in: Electronic Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1602.04387

zbMATH Keywords

asymptoticsnonparametric correlationdegeneracyU-statisticsHoeffding's Dtest of independence

Mathematics Subject Classification ID

Nonparametric hypothesis testing (62G10) Asymptotic properties of nonparametric inference (62G20) Order statistics; empirical distribution functions (62G30)

Related Items

Distribution-Free Consistent Independence Tests via Center-Outward Ranks and Signs, Exact detection thresholds and minimax optimality of Chatterjee's correlation coefficient, Testing independence in high dimensions with sums of rank correlations, High-dimensional consistent independence testing with maxima of rank correlations, Randomized incomplete \(U\)-statistics in high dimensions, A new coefficient of correlation, TauStar, Kernel-Based Tests for Joint Independence

Uses Software

• R
• energy
• TauStar

Cites Work

• Unnamed Item
• Measuring and testing dependence by correlation of distances
• Efficient computation of the Bergsma-Dassios sign covariance
• Symmetric statistics, Poisson point processes, and multiple Wiener integrals
• A consistent test of independence based on a sign covariance related to Kendall's tau
• Approximation Theorems of Mathematical Statistics
• Asymptotic Statistics
• Distribution Free Tests of Independence Based on the Sample Distribution Function
• A NEW MEASURE OF RANK CORRELATION
• A Non-Parametric Test of Independence
• A study of the power and robustness of a new test for independence against contiguous alternatives