On the identifiability and statistical features of a new distributional approach with reliability applications

Author:

Alnssyan Badr1ORCID,Ahmad Zubair2ORCID,Malela-Majika Jean-Claude3ORCID,Seong Jin-Taek4ORCID,Shafik Wasswa5ORCID

Affiliation:

1. Unit of Scientific Research, Applied College, Qassim University 1 , Buraydah 51452, Saudi Arabia

2. Department of Statistics, Quaid-i-Azam University 2 , Islamabad 44000, Pakistan

3. Department of Statistics, Faculty of Natural and Agricultural Sciences, University of Pretoria 3 , Hatfield, 0028 Pretoria, South Africa

4. Graduate School of Data Science, Chonnam National University 4 , Gwangju 61186, Republic of Korea

5. Dig Connectivity Research Laboratory (DCRLab), Ndejje University 5 , P.O. Box 600040, Kampala, Uganda

Abstract

Probability distributions have prominent applications in different sectors. Among these sectors, probability models are mostly used to analyze datasets in engineering. Among the existing probability distributions, the two-parameter Weibull model plays an important role in providing the best fit for engineering and other related datasets. This paper introduces a new method called a novel updated-W (denoted by “NU-W”) family of distributions that is used to develop a new updated form of the Weibull distribution. The proposed updated extension of the Weibull model is referred to as a novel updated Weibull (denoted as NU-Weibull) distribution. Distributional properties such as identifiability, heavy-tailed characteristic, and rth moment of the NU-W family are derived. The residual life analysis of the NU-Weibull distribution is provided. Finally, two physical applications from civil engineering and reliability sectors are analyzed to demonstrate the application and effectiveness of the NU-Weibull distribution. The data fitting results show that the NU-Weibull distribution is a more suitable and best fit for engineering datasets.

Funder

Qassim University

Publisher

AIP Publishing

Subject

General Physics and Astronomy

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