Estimation of Power Lomax Distribution for Censored Data With Applications
In this study, power Lomax (PL) distribution parameters are estimated under an adaptive Type-II progressive censoring scheme, utilizing both frequentist and Bayesian statistical estimations. The model parameters, reliability and hazard functions, and coefficient of variation are all determined using...
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| Format: | Article |
| Language: | English |
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Wiley
2025-01-01
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| Series: | Journal of Mathematics |
| Online Access: | http://dx.doi.org/10.1155/jom/3682098 |
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| author | Abdelfattah Mustafa Samah M. Ahmed |
| author_facet | Abdelfattah Mustafa Samah M. Ahmed |
| author_sort | Abdelfattah Mustafa |
| collection | DOAJ |
| description | In this study, power Lomax (PL) distribution parameters are estimated under an adaptive Type-II progressive censoring scheme, utilizing both frequentist and Bayesian statistical estimations. The model parameters, reliability and hazard functions, and coefficient of variation are all determined using an iterative procedure in the frequentist estimation. Furthermore, the asymptotic normality features of maximum likelihood estimates (MLEs) are used to calculate MLEs and asymptotic confidence intervals. The Bayesian method estimates under both symmetric and asymmetric loss functions by using the Markov Chain Monte Carlo (MCMC) technique. The performance of the Bayesian estimates and the MLEs is compared and contrasted in a simulated study. Finally, a numerical analysis of a real data set is presented to illustrate the application of the proposed inferential processes. |
| format | Article |
| id | doaj-art-a3a4bd2a1b45407fb6399b00f325493c |
| institution | Kabale University |
| issn | 2314-4785 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Mathematics |
| spelling | doaj-art-a3a4bd2a1b45407fb6399b00f325493c2025-08-20T03:28:06ZengWileyJournal of Mathematics2314-47852025-01-01202510.1155/jom/3682098Estimation of Power Lomax Distribution for Censored Data With ApplicationsAbdelfattah Mustafa0Samah M. Ahmed1Department of MathematicsDepartment of MathematicsIn this study, power Lomax (PL) distribution parameters are estimated under an adaptive Type-II progressive censoring scheme, utilizing both frequentist and Bayesian statistical estimations. The model parameters, reliability and hazard functions, and coefficient of variation are all determined using an iterative procedure in the frequentist estimation. Furthermore, the asymptotic normality features of maximum likelihood estimates (MLEs) are used to calculate MLEs and asymptotic confidence intervals. The Bayesian method estimates under both symmetric and asymmetric loss functions by using the Markov Chain Monte Carlo (MCMC) technique. The performance of the Bayesian estimates and the MLEs is compared and contrasted in a simulated study. Finally, a numerical analysis of a real data set is presented to illustrate the application of the proposed inferential processes.http://dx.doi.org/10.1155/jom/3682098 |
| spellingShingle | Abdelfattah Mustafa Samah M. Ahmed Estimation of Power Lomax Distribution for Censored Data With Applications Journal of Mathematics |
| title | Estimation of Power Lomax Distribution for Censored Data With Applications |
| title_full | Estimation of Power Lomax Distribution for Censored Data With Applications |
| title_fullStr | Estimation of Power Lomax Distribution for Censored Data With Applications |
| title_full_unstemmed | Estimation of Power Lomax Distribution for Censored Data With Applications |
| title_short | Estimation of Power Lomax Distribution for Censored Data With Applications |
| title_sort | estimation of power lomax distribution for censored data with applications |
| url | http://dx.doi.org/10.1155/jom/3682098 |
| work_keys_str_mv | AT abdelfattahmustafa estimationofpowerlomaxdistributionforcensoreddatawithapplications AT samahmahmed estimationofpowerlomaxdistributionforcensoreddatawithapplications |