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不确定性下的多变量分析:在化学含量数据中的应用

Multivariate Analysis under Indeterminacy: An Application to Chemical Content Data.

作者信息

Aslam Muhammad, Arif Osama H

机构信息

Department of Statistics, Faculty of Science, King Abdulaziz University, Jeddah 21551, Saudi Arabia.

Department of Mathematics, Faculty of Science, Jouf University, Sakakah, Saudi Arabia.

出版信息

J Anal Methods Chem. 2020 Jul 11;2020:1406028. doi: 10.1155/2020/1406028. eCollection 2020.

Abstract

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.

摘要

霍特林T平方统计量已被广泛用于多变量数据均值差异的检验。经典统计学中的现有统计量适用于多变量数据中的观测值是确定、精确且准确的情况。在实际中,由于复杂情况下的测量以及不确定性环境,数据中的所有观测值并非都必须是确定且精确的。在本文中,我们将介绍中智统计学(NS)下的霍特林T平方统计量,它是经典统计学的推广,适用于不确定性环境。我们将借助数据讨论中智霍特林T平方统计量的应用及优势。通过比较,我们将得出结论,所提出的统计量在不确定性方面更合适且有效。

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