A robust and nonparametric two-sample test in high dimensions

DOI10.5705/ss.202019.0170OpenAlexW3037979223MaRDI QIDQ5037790

Tao Qiu, Wang-li Xu, Li-ping Zhu

Publication date: 4 March 2022

Published in: Statistica Sinica (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.5705/ss.202019.0170

zbMATH Keywords

homogeneityU-statisticstwo-sample testhigh dimensionCramér-von Mises testequality of distributions

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (1)

Testing homogeneity in high dimensional data through random projections

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• A nonparametric two-sample test applicable to high dimensional data
• On high dimensional two-sample tests based on nearest neighbors
• Comparing distributions
• A multivariate two-sample test based on the number of nearest neighbor type coincidences
• Multivariate generalizations of the Wald-Wolfowitz and Smirnov two-sample tests
• On a new multivariate two-sample test.
• Ball divergence: nonparametric two sample test
• Conditional mean and quantile dependence testing in high dimension
• A two-sample test for high-dimensional data with applications to gene-set testing
• A distribution-free two-sample run test applicable to high-dimensional data
• Multivariate Two-Sample Tests Based on Nearest Neighbors
• Permutation tests for equality of distributions in high-dimensional settings
• Tests for High-Dimensional Regression Coefficients With Factorial Designs
• Testing Statistical Hypotheses
• An Exact Distribution-Free Test Comparing Two Multivariate Distributions based on Adjacency
• On the Distribution of the Two-Sample Cramer-von Mises Criterion
• Limit Theorems Associated with Variants of the Von Mises Statistic

This page was built for publication: A robust and nonparametric two-sample test in high dimensions