A New Power Topp-Leone distribution with applications to engineering and industry data

Mintodê Nicodème Atchadé; Melchior N'bouké; Aliou Moussa Djibril; Shabnam Shahzadi; Eslam Hussam; Ramy Aldallal; Huda M Alshanbari; Ahmed M Gemeay; Abdal-Aziz H El-Bagoury

doi:10.1371/journal.pone.0278225

A New Power Topp-Leone distribution with applications to engineering and industry data

PLoS One. 2023 Jan 17;18(1):e0278225. doi: 10.1371/journal.pone.0278225. eCollection 2023.

Authors

Affiliations

¹ National Higher School of Mathematics Genius and Modelization, National University of Sciences, Technologies, Engineering and Mathematics, Abomey, Benin Republic.
² University of Abomey-Calavi/International Chair in Mathematical Physics and Applications (ICMPA : UNESCO-Chair), Cotonou, Rep. Benin.
³ Department of Statistics and Econometrics, Saint-Petersburg State University of Economics, Saint-Petersburg, Russian Federation.
⁴ Department of Mathematics and Big Data, Anhui University of Science and Technology, Huainan, China.
⁵ Department of Mathmematics, Faculty of Science, Helwan University, Cairo, Egypt.
⁶ Department of Accounting, College of Business Administration in Hawtat Bani Tamim, Prince Sattam Abdulaziz University, Al-Kharj, Saudi Arabia.
⁷ Department of Mathematical Sciences, College of Science, Princess Nourah Bint Abdulrahman University, Riyadh, Saudi Arabia.
⁸ Department of Mathematics, Faculty of Science, Tanta University, Tanta, Egypt.
⁹ Basic Science Department, Higher Institute of Engineering and Technology, El-Mahala El-Kobra, Egypt.

Abstract

We introduced a brand-new member of the family that is going to be referred to as the New Power Topp-Leone Generated (NPTL-G). This new member is one of a kind. Given the major functions that created this new member, important mathematical aspects are discussed in as much detail as possible. We derived some functions for the new one, included the Rényi entropy, the qf, series development, and moment weighted probabilities. Moreover, to estimate the values of the parameters of our model that were not known, we employed the maximum likelihood technique. In addition, two actual datasets from the real world were investigated in order to bring attention to the possible applications of this novel distribution. This new model performs better than three key rivals based on the measurements that were collected.

Copyright: © 2023 Atchadé et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Entropy
Probability*

Grants and funding

Princess Nourah bint Abdulrahman University Researchers Supporting Project number (PNURSP2023R299), Princess Nourah Abdulrahman University, Riyadh, Saudi Arabia.