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Two-Sample Tests Based on Data Depth
In this paper, we focus on the homogeneity test that evaluates whether two multivariate samples come from the same distribution. This problem arises naturally in various applications, and there are many methods available in the literature. Based on data depth, several tests have been proposed for th...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9955243/ https://www.ncbi.nlm.nih.gov/pubmed/36832605 http://dx.doi.org/10.3390/e25020238 |
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author | Shi, Xiaoping Zhang, Yue Fu, Yuejiao |
author_facet | Shi, Xiaoping Zhang, Yue Fu, Yuejiao |
author_sort | Shi, Xiaoping |
collection | PubMed |
description | In this paper, we focus on the homogeneity test that evaluates whether two multivariate samples come from the same distribution. This problem arises naturally in various applications, and there are many methods available in the literature. Based on data depth, several tests have been proposed for this problem but they may not be very powerful. In light of the recent development of data depth as an important measure in quality assurance, we propose two new test statistics for the multivariate two-sample homogeneity test. The proposed test statistics have the same [Formula: see text] asymptotic null distribution. The generalization of the proposed tests into the multivariate multisample situation is discussed as well. Simulations studies demonstrate the superior performance of the proposed tests. The test procedure is illustrated through two real data examples. |
format | Online Article Text |
id | pubmed-9955243 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-99552432023-02-25 Two-Sample Tests Based on Data Depth Shi, Xiaoping Zhang, Yue Fu, Yuejiao Entropy (Basel) Article In this paper, we focus on the homogeneity test that evaluates whether two multivariate samples come from the same distribution. This problem arises naturally in various applications, and there are many methods available in the literature. Based on data depth, several tests have been proposed for this problem but they may not be very powerful. In light of the recent development of data depth as an important measure in quality assurance, we propose two new test statistics for the multivariate two-sample homogeneity test. The proposed test statistics have the same [Formula: see text] asymptotic null distribution. The generalization of the proposed tests into the multivariate multisample situation is discussed as well. Simulations studies demonstrate the superior performance of the proposed tests. The test procedure is illustrated through two real data examples. MDPI 2023-01-28 /pmc/articles/PMC9955243/ /pubmed/36832605 http://dx.doi.org/10.3390/e25020238 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Shi, Xiaoping Zhang, Yue Fu, Yuejiao Two-Sample Tests Based on Data Depth |
title | Two-Sample Tests Based on Data Depth |
title_full | Two-Sample Tests Based on Data Depth |
title_fullStr | Two-Sample Tests Based on Data Depth |
title_full_unstemmed | Two-Sample Tests Based on Data Depth |
title_short | Two-Sample Tests Based on Data Depth |
title_sort | two-sample tests based on data depth |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9955243/ https://www.ncbi.nlm.nih.gov/pubmed/36832605 http://dx.doi.org/10.3390/e25020238 |
work_keys_str_mv | AT shixiaoping twosampletestsbasedondatadepth AT zhangyue twosampletestsbasedondatadepth AT fuyuejiao twosampletestsbasedondatadepth |