An approximate randomization test for the high-dimensional two-sample Behrens–Fisher problem under arbitrary covariances

DOI10.1093/BIOMET/ASAC014OpenAlexW4213269024WikidataQ115582925 ScholiaQ115582925MaRDI QIDQ5872854

Rui Wang, Wang-li Xu

Publication date: 4 January 2023

Published in: Biometrika (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2108.01860

zbMATH Keywords

high-dimensional datarandomization testBehrens-Fisher problemLindeberg principle

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (3)

Two-sample test for high-dimensional covariance matrices: a normal-reference approach ⋮ Tests for high-dimensional generalized linear models under general covariance structure ⋮ A new test for high-dimensional two-sample mean problems with consideration of correlation structure

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