Large dimensional Spearman's rank correlation matrices: The central limit theorem and its applications

Fuente: arXiv
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Autori principali: Chen, Hantao, Wang, Cheng
Natura: Preprint
Pubblicazione: 2024
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author Chen, Hantao
Wang, Cheng
author_facet Chen, Hantao
Wang, Cheng
contents This paper is concerned with Spearman's correlation matrices under large dimensional regime, in which the data dimension diverges to infinity proportionally with the sample size. We establish the central limit theorem for the linear spectral statistics of Spearman's correlation matrices, which extends the results of [\emph{Ann. Statist.} 43(2015) 2588--2623]. We also study the improved Spearman's correlation matrices [\emph{Ann. Math. Statist} 19(1948) 293--325] which is a standard U-statistic of order 3. As applications, we propose three new test statistics for large dimensional independent test and numerical studies demonstrate the applicability of our proposed methods.
format Preprint
id arxiv_https___arxiv_org_abs_2411_15861
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Large dimensional Spearman's rank correlation matrices: The central limit theorem and its applications
Chen, Hantao
Wang, Cheng
Statistics Theory
62H15, 62H20, 62G30, 62G35
This paper is concerned with Spearman's correlation matrices under large dimensional regime, in which the data dimension diverges to infinity proportionally with the sample size. We establish the central limit theorem for the linear spectral statistics of Spearman's correlation matrices, which extends the results of [\emph{Ann. Statist.} 43(2015) 2588--2623]. We also study the improved Spearman's correlation matrices [\emph{Ann. Math. Statist} 19(1948) 293--325] which is a standard U-statistic of order 3. As applications, we propose three new test statistics for large dimensional independent test and numerical studies demonstrate the applicability of our proposed methods.
title Large dimensional Spearman's rank correlation matrices: The central limit theorem and its applications
topic Statistics Theory
62H15, 62H20, 62G30, 62G35
url https://arxiv.org/abs/2411.15861