Testing high-dimensional covariance matrices under the elliptical distribution and beyond

DOI10.1016/j.jeconom.2020.05.017zbMath1471.62381arXiv1707.04010OpenAlexW3047836600MaRDI QIDQ2658752

Xinxin Yang, Jiaqi Chen, Xinghua Zheng

Publication date: 24 March 2021

Published in: Journal of Econometrics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1707.04010

zbMATH Keywords

covariance matrixcentral limit theoremhigh-dimensionlinear spectral statisticselliptical model

Mathematics Subject Classification ID

Multivariate distribution of statistics (62H10) Asymptotic distribution theory in statistics (62E20) Applications of statistics to actuarial sciences and financial mathematics (62P05) Hypothesis testing in multivariate analysis (62H15) Central limit and other weak theorems (60F05)

Related Items (5)

Tracy-Widom limit for the largest eigenvalue of high-dimensional covariance matrices in elliptical distributions ⋮ Likelihood ratio tests for elaborate covariance structures and for MANOVA models with elaborate covariance structures -- a review ⋮ A bootstrap method for spectral statistics in high-dimensional elliptical models ⋮ Global one-sample tests for high-dimensional covariance matrices ⋮ Likelihood ratio tests under model misspecification in high dimensions

Uses Software

• QRM

Cites Work

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