Estimation of Power Lomax Distribution for Censored Data With Applications

Abdelfattah Mustafa and Samah M. Ahmed

Journal of Mathematics, 2025, vol. 2025, 1-14

Abstract: 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.

Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://downloads.hindawi.com/journals/jmath/2025/3682098.pdf (application/pdf)
http://downloads.hindawi.com/journals/jmath/2025/3682098.xml (application/xml)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hin:jjmath:3682098

DOI: 10.1155/jom/3682098

Access Statistics for this article

More articles in Journal of Mathematics from Hindawi
Bibliographic data for series maintained by Mohamed Abdelhakeem ().