Paper Type ![]() |
Contributed Paper |
Title ![]() |
Inverse Power Generalized Maxwell Distribution with Applications in Industry |
Author ![]() |
Ahmed M. Gemeay, Hebatalla H. Mohammad, Abeer A. EL-Helbawy, Laxmi Prasad Sapkota, Sid Ahmed Benchiha, Eslam Hussam and Mustafa S. Shama |
Email ![]() |
laxmisapkota75@gmail.com |
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. |
|
Graphical Abstract: |
|
Article ID ![]() |
e2025063 |
Received Date ![]() |
2025-02-15 |
Revised Date ![]() |
2025-06-11 |
Accepted Date ![]() |
2025-07-01 |
Keyword ![]() |
generalize maxwell distribution, moments, estimation, inverse power, entropy |
Volume ![]() |
Vol.52 No.5 In progress (September 2025). This issue is in progress but contains articles that are final and fully citable. |
DOI |
https://doi.org/10.12982/CMJS.2025.063 |
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. |
View:44 Download:0 |