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A Class of Association Measures for Categorical Variables Based on Weighted Minkowski Distance
Measuring and testing association between categorical variables is one of the long-standing problems in multivariate statistics. In this paper, I define a broad class of association measures for categorical variables based on weighted Minkowski distance. The proposed framework subsumes some importan...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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MDPI
2019
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7514322/ http://dx.doi.org/10.3390/e21100990 |
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author | Zhang, Qingyang |
author_facet | Zhang, Qingyang |
author_sort | Zhang, Qingyang |
collection | PubMed |
description | Measuring and testing association between categorical variables is one of the long-standing problems in multivariate statistics. In this paper, I define a broad class of association measures for categorical variables based on weighted Minkowski distance. The proposed framework subsumes some important measures including Cramér’s V, distance covariance, total variation distance and a slightly modified mean variance index. In addition, I establish the strong consistency of the defined measures for testing independence in two-way contingency tables, and derive the scaled forms of unweighted measures. |
format | Online Article Text |
id | pubmed-7514322 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-75143222020-11-09 A Class of Association Measures for Categorical Variables Based on Weighted Minkowski Distance Zhang, Qingyang Entropy (Basel) Article Measuring and testing association between categorical variables is one of the long-standing problems in multivariate statistics. In this paper, I define a broad class of association measures for categorical variables based on weighted Minkowski distance. The proposed framework subsumes some important measures including Cramér’s V, distance covariance, total variation distance and a slightly modified mean variance index. In addition, I establish the strong consistency of the defined measures for testing independence in two-way contingency tables, and derive the scaled forms of unweighted measures. MDPI 2019-10-11 /pmc/articles/PMC7514322/ http://dx.doi.org/10.3390/e21100990 Text en © 2019 by the author. 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 (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Zhang, Qingyang A Class of Association Measures for Categorical Variables Based on Weighted Minkowski Distance |
title | A Class of Association Measures for Categorical Variables Based on Weighted Minkowski Distance |
title_full | A Class of Association Measures for Categorical Variables Based on Weighted Minkowski Distance |
title_fullStr | A Class of Association Measures for Categorical Variables Based on Weighted Minkowski Distance |
title_full_unstemmed | A Class of Association Measures for Categorical Variables Based on Weighted Minkowski Distance |
title_short | A Class of Association Measures for Categorical Variables Based on Weighted Minkowski Distance |
title_sort | class of association measures for categorical variables based on weighted minkowski distance |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7514322/ http://dx.doi.org/10.3390/e21100990 |
work_keys_str_mv | AT zhangqingyang aclassofassociationmeasuresforcategoricalvariablesbasedonweightedminkowskidistance AT zhangqingyang classofassociationmeasuresforcategoricalvariablesbasedonweightedminkowskidistance |