High-dimensional consistent independence testing with maxima of rank correlations
From MaRDI portal
Publication:1996766
DOI10.1214/19-AOS1926zbMath1461.62078arXiv1812.06189OpenAlexW3111233659MaRDI QIDQ1996766
Fang Han, Hongjian Shi, Mathias Drton
Publication date: 26 February 2021
Published in: The Annals of Statistics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1812.06189
extreme value distributionindependence testrank statisticsdegenerate U-statisticsmaximum-type testrate-optimality
Hypothesis testing in multivariate analysis (62H15) Measures of association (correlation, canonical correlation, etc.) (62H20) Characterization and structure theory for multivariate probability distributions; copulas (62H05) Statistics of extreme values; tail inference (62G32) Large deviations (60F10)
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The Binary Expansion Randomized Ensemble Test, Max-sum test based on Spearman's footrule for high-dimensional independence tests, Hypothesis Tests for Structured Rank Correlation Matrices, Rank-based indices for testing independence between two high-dimensional vectors, Testing for independence in high dimensions based on empirical copulas, Rank-based max-sum tests for mutual independence of high-dimensional random vectors, Exact detection thresholds and minimax optimality of Chatterjee's correlation coefficient, Counterexamples to the classical central limit theorem for triplewise independent random variables having a common arbitrary margin, On universally consistent and fully distribution-free rank tests of vector independence
Uses Software
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