An adaptive spatial-sign-based test for mean vectors of elliptically distributed high-dimensional data

DOI10.4310/SII.2019.v12.n1.a9WikidataQ129036326 ScholiaQ129036326MaRDI QIDQ1624312

Jin-Ting Zhang, Jianwei Chen, Bu Zhou, Jia Guo

Publication date: 16 November 2018

Published in: Statistics and Its Interface (Search for Journal in Brave)

zbMATH Keywords

high-dimensional dataWelch-Satterthwaite \(\chi^2\)-approximationspatial-sign-based test

Mathematics Subject Classification ID

Nonparametric hypothesis testing (62G10) Hypothesis testing in multivariate analysis (62H15)

Related Items (4)

Testing high-dimensional mean vector with applications. A normal reference approach ⋮ Linear hypothesis testing in high-dimensional heteroscedastic one-way MANOVA: a normal reference \(L^2\)-norm based test ⋮ Recent developments in high-dimensional inference for multivariate data: parametric, semiparametric and nonparametric approaches ⋮ High-dimensional MANOVA under weak conditions

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