| Title: Bayesian Estimation of the Lomax Distribution Parameters under Progressive Type-II Censoring |
| Paper ID : 1001-ISCH |
| Authors |
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NADIYAH MUNAHI ALMUTAIRI * M.Sc. Student, Department of Statistics, Faculty of Science, Helwan University |
| Abstract |
| In this paper, approximate Bayesian estimators for the unknown parameters of the Lomax distribution are developed using progressive Type-II censored samples. The research examines both maximum likelihood and Bayesian estimation techniques, with the latter incorporating gamma-informative prior distributions for the parameters. Additionally, the reliability function and reversed hazard rate function are investigated. To calculate the Bayesian estimates, Lindley’s approximation (1980) and Markov Chain Monte Carlo (MCMC) methods are utilized. The estimators are derived under symmetric and asymmetric loss functions, such as the linex and general entropy loss functions. A simulation study is conducted to evaluate the effectiveness of the proposed estimators, and numerical results are presented to illustrate their performance. The results reveal that Bayesian estimators generally outperform classical ones under certain conditions, especially when prior information is accurate. The methods discussed are useful in reliability analysis, risk assessment, and survival studies, where censored data frequently arise. This research contributes to the growing literature on Bayesian analysis for lifetime distributions with censored observations. |
| Keywords |
| Bayesian Estimation of the Lomax Distribution Parameters under Progressive Type-II Censoring |
| Status: Abstract Accepted (Oral Presentation) |