A generalized Wilcoxon-Mann-Whitney type test for multivariate data through pairwise distance

DOI10.1016/j.jmva.2022.104946zbMath1493.62346OpenAlexW4206960538MaRDI QIDQ2140849

Shuangge Ma, Jiamin Liu, Li-ping Zhu, Wang-li Xu

Publication date: 23 May 2022

Published in: Journal of Multivariate Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jmva.2022.104946

zbMATH Keywords

homogeneitytwo-sample testWilcoxon-Mann-Whitney testpairwise distancerank sum

Mathematics Subject Classification ID

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

Cites Work

• Unnamed Item
• Unnamed Item
• Consistency of general bootstrap methods for degenerate \(U\)-type and \(V\)-type statistics
• Functional limit theorems for U-statistics in the degenerate case
• Ball divergence: nonparametric two sample test
• The multivariate nonparametric Behrens-Fisher problem
• A rank-based Cramér-von-Mises-type test for two samples
• A \(U\)-statistic approach for a high-dimensional two-sample mean testing problem under non-normality and Behrens-Fisher setting
• A two-sample test for location
• A class of two-sample tests for location based on sub-sample medians
• An Approach to Multivariate Rank Tests in Multivariate Analysis of Variance
• Permutation tests for equality of distributions in high-dimensional settings
• A New Class of Distribution-Free Tests for Location Parameters
• A Quality Index Based on Data Depth and Multivariate Rank Tests
• A Wilcoxon-Mann-Whitney-type test for infinite-dimensional data
• On a Test of Whether one of Two Random Variables is Stochastically Larger than the Other
• Modified Wilcoxon–Mann–Whitney Test and Power Against Strong Null