| dc.contributor.author | Abdelfattah Mustafa | |
| dc.contributor.author | M. I. Khan | |
| dc.contributor.author | Samah M. Ahmed | |
| dc.contributor.other | Mathematics Department, Faculty of Science, Islamic University of Madinah, Madinah 42351, Saudi Arabia | |
| dc.contributor.other | Mathematics Department, Faculty of Science, Islamic University of Madinah, Madinah 42351, Saudi Arabia | |
| dc.contributor.other | Mathematics Department, Faculty of Science, Sohag University, Sohag 82524, Egypt | |
| dc.date.accessioned | 2025-08-27T02:32:32Z | |
| dc.date.accessioned | 2025-10-08T08:04:22Z | |
| dc.date.available | 2025-10-08T08:04:22Z | |
| dc.date.issued | 2025-07 | |
| dc.identifier.uri | https://www.aimspress.com/article/doi/10.3934/math.2025700 | |
| dc.identifier.uri | http://digilib.fisipol.ugm.ac.id/repo/handle/15717717/35579 | |
| dc.description.abstract | This research focused on estimating the stress-strength parameter by considering stress and strength as distinct random variables, both characterized by the inverse power Lomax (IPL) distribution. The maximum likelihood estimate (MLE) for stress-strength reliability was then calculated using the Newton-Raphson method. Using the asymptotic normality of MLEs, this study developed approximate confidence intervals. Bootstrap confidence intervals for the stress-strength reliability parameter ($ R $) were investigated. The Bayes estimator of $ R $ was considered. Furthermore, we utilized the Markov chain Monte Carlo (MCMC) method to create both symmetric and asymmetric loss functions, allowing for a more comprehensive analysis. The highest posterior density (HPD) credible intervals under a gamma prior distribution were calculated. The different approaches were assessed using a Monte Carlo simulation. Finally, a numerical example was given to show the effectiveness of the proposed methods. | |
| dc.language.iso | EN | |
| dc.publisher | AIMS Press | |
| dc.subject.lcc | Mathematics | |
| dc.title | Estimating the stress-strength reliability parameter of the inverse power Lomax distribution | |
| dc.type | Article | |
| dc.description.keywords | maximum likelihood estimator | |
| dc.description.keywords | the inverse power lomax model | |
| dc.description.keywords | stress-strength reliability | |
| dc.description.keywords | symmetric and asymmetric loss functions | |
| dc.description.keywords | bootstrap resampling | |
| dc.description.keywords | bayes estimator | |
| dc.description.pages | 15632-15652 | |
| dc.description.doi | 10.3934/math.2025700 | |
| dc.title.journal | AIMS Mathematics | |
| dc.identifier.e-issn | 2473-6988 | |
| dc.identifier.oai | 09802376901442f3834f3edc4ab54e5c | |
| dc.journal.info | Volume 10, Issue 7 | |
