Generalized Pareto Model: Properties and Applications in Neutrosophic Data Modeling

被引：0

作者：

Khan Z. ^{[1
]}

Almazah M.M.A. ^{[2
]}

Hamood Odhah O. ^{[3
]}

Alshanbari H.M. ^{[3
]}

机构：

[1] Department of Mathematics and Statistics, Hazara University Mansehra, Mansehra

[2] Department of Mathematics, College of Sciences and Arts (Muhyil), King Khalid University, Muhyil

[3] Department of Mathematical Sciences, College of Science, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh

来源：

Mathematical Problems in Engineering | 2022年 / 2022卷

关键词：

Compendex;

D O I：

10.1155/2022/3686968

中图分类号：

学科分类号：

摘要：

The Pareto distribution is widely used to model industrial, biological, engineering, and other various types of data. A new generalized model, namely the neutrosophic Pareto distribution (NPD), is developed in this article. The proposed model is a neutrosophic variant of the classical Pareto distribution, potentially useful for analyzing vague, unclear, indeterminate, or imprecise data. The structure form of the proposed distribution is skewed to the right and determined to be unimodal. Several characteristics of the NPD are investigated under the neutrosophic framework. The expressions for basic properties such as mean, variance, raw moments, and shape coefficients are obtained. The maximum likelihood approach is presented for estimating the imprecise distributional parameters of the proposed model. The extended notions of the NPD are explained with various key functions in the domain of applied statistical methods. Finally, the practical benefits of NPD are proven by analyzing two real datasets. © 2022 Zahid Khan et al.

引用

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