Estimation of the Gompertz Distribution Parameters under Joint Progressive Censoring Data
| dc.contributor.author | KETTOUCHE, Karima | |
| dc.contributor.author | BOUTOBZA ,Roqiya | |
| dc.contributor.author | BOULKEROUA, Fouzia | |
| dc.date.accessioned | 2024-04-25T07:29:29Z | |
| dc.date.available | 2024-04-25T07:29:29Z | |
| dc.date.issued | 2023 | |
| dc.description.abstract | This thesis aims to estimate the Gompertz distributions parameters using the joint progressive type-II censoring scheme. For the estimate problem, the likeli- hood, Bootstrap, and Bayesian approaches are used. We employ various numeri- cal methods, such Newton-Raphson, to solve the likelihood equations because the resulting maximum likelihood estimators are not written in closed forms. Addi- tionally, we take into account the Bayesian method for estimating the unknown parameters while using independent gamma priors for the scale and shape pa- rameters. We employ importance sampling and Metropolis-Hastings approaches in the Bayesian analysis, which are based on symmetric and asymmetric loss functions. Furthermore, credible intervals based on the Bayesian method and confidence intervals based on asymptotic normality are presented. To compare the performance of the proposed methods, a Monte Carlo simulation is run, and real-life data is examined for illustrative purposes. | |
| dc.identifier.uri | http://dspace.univ-skikda.dz:4000/handle/123456789/1386 | |
| dc.language.iso | en | |
| dc.publisher | Faculty of Sciences | |
| dc.title | Estimation of the Gompertz Distribution Parameters under Joint Progressive Censoring Data | |
| dc.title.alternative | Numerical Analysis, PDE and Applications | |
| dc.type | Master's degree diploma |