AIP Advances (Dec 2023)

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

  • Badr Alnssyan,
  • Zubair Ahmad,
  • Jean-Claude Malela-Majika,
  • Jin-Taek Seong,
  • Wasswa Shafik

DOI
https://doi.org/10.1063/5.0178555
Journal volume & issue
Vol. 13, no. 12
pp. 125211 – 125211-15

Abstract

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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.