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Multivariate Analysis under Indeterminacy: An Application to Chemical Content Data

The Hotelling T-squared statistic has been widely used for the testing of differences in means for the multivariate data. The existing statistic under classical statistics is applied when observations in multivariate data are determined, precise, and exact. In practice, it is not necessary that all...

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Autores principales: Aslam, Muhammad, Arif, Osama H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7369667/
https://www.ncbi.nlm.nih.gov/pubmed/32733737
http://dx.doi.org/10.1155/2020/1406028
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author Aslam, Muhammad
Arif, Osama H.
author_facet Aslam, Muhammad
Arif, Osama H.
author_sort Aslam, Muhammad
collection PubMed
description The Hotelling T-squared statistic has been widely used for the testing of differences in means for the multivariate data. The existing statistic under classical statistics is applied when observations in multivariate data are determined, precise, and exact. In practice, it is not necessary that all observations in the data are determined and precise due to measurement in complex situations and under uncertainty environment. In this paper, we will introduce the Hotelling T-squared statistic under neutrosophic statistics (NS) which is the generalization of classical statistics and applied under uncertainty environment. We will discuss the application and advantage of the neutrosophic Hotelling T-squared statistic with the aid of data. From the comparison, we will conclude that the proposed statistic is more adequate and effective in uncertainty.
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spelling pubmed-73696672020-07-29 Multivariate Analysis under Indeterminacy: An Application to Chemical Content Data Aslam, Muhammad Arif, Osama H. J Anal Methods Chem Research Article The Hotelling T-squared statistic has been widely used for the testing of differences in means for the multivariate data. The existing statistic under classical statistics is applied when observations in multivariate data are determined, precise, and exact. In practice, it is not necessary that all observations in the data are determined and precise due to measurement in complex situations and under uncertainty environment. In this paper, we will introduce the Hotelling T-squared statistic under neutrosophic statistics (NS) which is the generalization of classical statistics and applied under uncertainty environment. We will discuss the application and advantage of the neutrosophic Hotelling T-squared statistic with the aid of data. From the comparison, we will conclude that the proposed statistic is more adequate and effective in uncertainty. Hindawi 2020-07-11 /pmc/articles/PMC7369667/ /pubmed/32733737 http://dx.doi.org/10.1155/2020/1406028 Text en Copyright © 2020 Muhammad Aslam and Osama H. Arif. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Aslam, Muhammad
Arif, Osama H.
Multivariate Analysis under Indeterminacy: An Application to Chemical Content Data
title Multivariate Analysis under Indeterminacy: An Application to Chemical Content Data
title_full Multivariate Analysis under Indeterminacy: An Application to Chemical Content Data
title_fullStr Multivariate Analysis under Indeterminacy: An Application to Chemical Content Data
title_full_unstemmed Multivariate Analysis under Indeterminacy: An Application to Chemical Content Data
title_short Multivariate Analysis under Indeterminacy: An Application to Chemical Content Data
title_sort multivariate analysis under indeterminacy: an application to chemical content data
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7369667/
https://www.ncbi.nlm.nih.gov/pubmed/32733737
http://dx.doi.org/10.1155/2020/1406028
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