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Reliability Analysis and Parameter Estimation for Censored Data in Extended Gompertz Distribution |
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PP: 433-452 |
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doi:10.18576/jsap/140307
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Author(s) |
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N. Abozeid,
M. M. Nassar,
S. E. Abu-Youssef,
R. M. EL-Sagheer,
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Abstract |
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| This article explores the estimation of parameters and lifetime indices of the extended Gompertz distribution under progressively Type-II censored schemes. The study employs maximum likelihood, Bayes, and two parametric bootstrap methods for parameter estimation, alongside the computation of reliability and hazard rate functions. Additionally, approximate confidence intervals and an asymptotic variance-covariance matrix are derived. The Markov chain Monte Carlo technique, specifically the Gibbs sampler within the Metropolis-Hastings algorithm, is utilized to generate samples from posterior density functions. Bayesian estimates are computed using both symmetric and asymmetric loss functions. Through Monte Carlo simulations, the efficacy of these methods is evaluated using metrics such as mean squared errors, average interval lengths, and coverage probabilities. Finally, a real dataset is analyzed to demonstrate the practical application of the developed inferential procedures.
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