A note on high-dimensional two-sample test

DOI10.1016/j.spl.2015.05.017zbMath1327.62352OpenAlexW863497847MaRDI QIDQ894570

Fasheng Sun, Long Feng

Publication date: 1 December 2015

Published in: Statistics \& Probability Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.spl.2015.05.017

zbMATH Keywords

Behrens-Fisher problemlarge \(p\), small \(n\)scalar-invariant

Mathematics Subject Classification ID

Hypothesis testing in multivariate analysis (62H15)

Related Items (12)

Testing linear hypothesis of high-dimensional means with unequal covariance matrices ⋮ Hotelling's \(T^2\) in separable Hilbert spaces ⋮ High-dimensional general linear hypothesis testing under heteroscedasticity ⋮ High-Dimensional MANOVA Via Bootstrapping and Its Application to Functional and Sparse Count Data ⋮ Two-sample Behrens–Fisher problems for high-dimensional data: a normal reference scale-invariant test ⋮ A high‐dimensional inverse norm sign test for two‐sample location problems ⋮ A Pairwise Hotelling Method for Testing High-Dimensional Mean Vectors ⋮ Linear hypothesis testing in high-dimensional one-way MANOVA ⋮ A review of 20 years of naive tests of significance for high-dimensional mean vectors and covariance matrices ⋮ A high-dimensional spatial rank test for two-sample location problems ⋮ Recent developments in high-dimensional inference for multivariate data: parametric, semiparametric and nonparametric approaches ⋮ High-dimensional MANOVA under weak conditions

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