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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...

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Detalles Bibliográficos
Autores principales: Shi, Xiaoping, Zhang, Yue, Fu, Yuejiao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
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.
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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
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