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

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Authors

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

Journal Title

Journal ISSN

Volume Title

Publisher

American Institute of Physics

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, heavytailed 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.

Description

DATA AVAILABILITY : The datasets that support the findings of this study are provided within the article.

Keywords

Probability distributions, Sectors, Engineering, Weibull model

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None

Citation

Alnssyan, B., Ahmad, Z., Malela-Majika, J.C. et al. 2023, 'On the identifiability and statistical features of a new distributional approach with reliability applications', AIP Advances, vol. 13, no. 12, art. 125211, pp. 1-15, doi : 10.1063/5.0178555.