Two-sample Behrens-Fisher problems for high-dimensional data: a normal reference approach

DOI10.1016/j.jspi.2020.11.008zbMath1465.62186OpenAlexW3106637505MaRDI QIDQ830717

Tianming Zhu, Bu Zhou, Jin-Ting Zhang, Jia Guo

Publication date: 7 May 2021

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jspi.2020.11.008

zbMATH Keywords

Welch-Satterthwaite \(\chi^2\)-approximation\( \chi^2\)-type mixtures\( L^2\)-norm-based testhigh-dimensional Behrens-Fisher problem

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Hypothesis testing in multivariate analysis (62H15) Medical epidemiology (92C60) Statistical aspects of big data and data science (62R07)

Related Items (6)

A high-dimensional test for the k-sample Behrens–Fisher problem ⋮ A Behrens-Fisher problem for general factor models in high dimensions ⋮ Linear hypothesis testing in high-dimensional heteroscedastic one-way MANOVA: a normal reference \(L^2\)-norm based test ⋮ A further study on Chen-Qin's test for two-sample Behrens-Fisher problems for high-dimensional data ⋮ A new normal reference test for linear hypothesis testing in high-dimensional heteroscedastic one-way MANOVA ⋮ A revisit to Bai–Saranadasa's two-sample test

Cites Work

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