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Generalized Pareto Model: Properties and Applications in Neutrosophic Data Modeling

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  • Zahid Khan
  • Mohammed M. A. Almazah
  • Omalsad Hamood Odhah
  • Huda M. Alshanbari
  • Tahir Mehmood

Abstract

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.

Suggested Citation

  • Zahid Khan & Mohammed M. A. Almazah & Omalsad Hamood Odhah & Huda M. Alshanbari & Tahir Mehmood, 2022. "Generalized Pareto Model: Properties and Applications in Neutrosophic Data Modeling," Mathematical Problems in Engineering, Hindawi, vol. 2022, pages 1-11, September.
    • Handle: RePEc:hin:jnlmpe:3686968
    DOI: 10.1155/2022/3686968
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