A robust test for sphericity of high-dimensional covariance matrices

DOI10.1016/j.jmva.2015.07.010zbMath1327.62356OpenAlexW1086307340MaRDI QIDQ746886

Xintao Tian, Wei-Ming Li, Yu-Ting Lu

Publication date: 21 October 2015

Published in: Journal of Multivariate Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jmva.2015.07.010

zbMATH Keywords

covariance matrixhigh-dimensional datasphericity test

Mathematics Subject Classification ID

Multivariate distribution of statistics (62H10) Hypothesis testing in multivariate analysis (62H15)

Related Items (8)

A supplement on CLT for LSS under a large dimensional generalized spiked covariance model ⋮ Testing high dimensional covariance matrices via posterior Bayes factor ⋮ A bootstrap method for spectral statistics in high-dimensional elliptical models ⋮ Central limit theorem of linear spectral statistics of high-dimensional sample correlation matrices ⋮ High-dimensional covariance matrices in elliptical distributions with application to spherical test ⋮ Sphericity and identity test for high-dimensional covariance matrix using random matrix theory ⋮ Some sphericity tests for high dimensional data based on ratio of the traces of sample covariance matrices ⋮ High-dimensional sphericity test by extended likelihood ratio

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