Testing the sphericity of a covariance matrix when the dimension is much larger than the sample size

DOI10.1214/16-EJS1199zbMath1353.62063arXiv1508.02498MaRDI QIDQ502778

Zeng Li, Jian-feng Yao

Publication date: 11 January 2017

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

Full work available at URL: https://arxiv.org/abs/1508.02498

zbMATH Keywords

sphericity testJohn's testquasi-likelihood ratio testlarge dimensionultra-dimension

Mathematics Subject Classification ID

Multivariate distribution of statistics (62H10) Hypothesis testing in multivariate analysis (62H15) Asymptotic properties of parametric tests (62F05)

Related Items (6)

Testing high dimensional covariance matrices via posterior Bayes factor ⋮ Adaptive Tests for Bandedness of High-dimensional Covariance Matrices ⋮ Asymptotic normality for eigenvalue statistics of a general sample covariance matrix when \(p/n \to \infty\) and applications ⋮ On testing the equality of latent roots of scatter matrices under ellipticity ⋮ Accuracy of regularized D-rule for binary classification ⋮ High-dimensional sphericity test by extended likelihood ratio

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