Chiang Mai Journal of Science

Print ISSN: 0125-2526 | eISSN : 2465-3845

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Inverse Power Generalized Maxwell Distribution with Applications in Industry

Ahmed M. Gemeay, Hebatalla H. Mohammad, Abeer A. EL-Helbawy, Laxmi Prasad Sapkota, Sid Ahmed Benchiha, Eslam Hussam and Mustafa S. Shama
* Author for corresponding; e-mail address: laxmisapkota75@gmail.com
Volume: Vol.52 No.5 (September 2025)
Research Article
DOI: https://doi.org/10.12982/CMJS.2025.063
Received: 15 Febuary 2025, Revised: 11 June 2025, Accepted: 1 July 2025, Published: 26 August 2025

Citation: Gemeay A.M., Mohammad H.H., EL-Helbawy A.A., Sapkota L.P., Benchiha S.A., Hussam E., et al., Inverse power generalized Maxwell distribution with applications in industry. Chiang Mai Journal of Science, 2025; 52(5): e2025063. DOI 10.12982/CMJS.2025.063.

Graphical Abstract

Graphical Abstract

Abstract

     Utilizing the inverse power transformation methodology, we introduce a novel continuous three-parameter probability distribution termed the inverse power generalized Maxwell distribution, which extends upon the existing Maxwell distribution. In this paper, we establish Key functions relevant to survival analysis and elucidate various statistical properties of the model. Our investigation delves into the estimation of model parameters by employing and rigorously evaluating six distinct estimation techniques through extensive numerical simulations. To assess the practical utility of the proposed model, we analyze two real-world engineering datasets. Empirically, the results demonstrate that the proposed model provides a superior goodness-of-fit compared to alternative models considered in this study.

Keywords: generalize maxwell distribution, moments, estimation, inverse power, entropy

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