Asymptotic linear dependence and ellipse statistics for multivariate two-sample homogeneity test

Statistical depth, which measures the center-outward rank of a given sample with respect to its underlying distribution, has become a popular and powerful tool in nonparametric inference. In this paper, we investigate the use of statistical depth in multivariate two-sample problems. We propose a new depth-based nonparametric two-sample test, which has the Chi-square(1) asymptotic distribution under the null hypothesis. Simulations and real-data applications highlight the efficacy and practical value of the proposed test.

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Publication Details

Journal
Communication in Statistics- Theory and Methods
Published
2026-10-16
DOI
https://doi.org/10.1080/03610926.2026.2743000
Primary Topic
Advanced Statistical Methods and Models
Type
article
Field-Weighted Citation Impact
0.00

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article

Asymptotic linear dependence and ellipse statistics for multivariate two-sample homogeneity test

Communication in Statistics- Theory and Methods
Advanced Statistical Methods and Models
article

Asymptotic linear dependence and ellipse statistics for multivariate two-sample homogeneity test

article en

Abstract

Statistical depth, which measures the center-outward rank of a given sample with respect to its underlying distribution, has become a popular and powerful tool in nonparametric inference. In this paper, we investigate the use of statistical depth in multivariate two-sample problems. We propose a new depth-based nonparametric two-sample test, which has the Chi-square(1) asymptotic distribution under the null hypothesis. Simulations and real-data applications highlight the efficacy and practical value of the proposed test.

Communication in Statistics- Theory and Methods
University of British Columbia (CA), York University (CA), University of York (GB)
University of British Columbia, Natural Sciences and Engineering Research Council of Canada
Openalex Percentile: Top 94%
Advanced Statistical Methods and Models
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