The Bayesian Estimation and Prediction Process Applied to a Mixture of Weibull and Gompertz Distributions Based on Type-I censoring | ||||
Al-Azhar Bulletin of Science | ||||
Volume 2024, Issue 1, January 2024 | ||||
DOI: 10.58675/2636-3305.1685 | ||||
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Authors | ||||
M. M. Mohie El-Din; A. Sadek; A. AL-Dugin | ||||
Dept. of Math., Faculty of Science, Al-Azhar University, Nasr City, Cairo, Egypt | ||||
Abstract | ||||
We examine different methods to estimate the parameters of a lifetime model represented by a mixture of Weibull and Gompertz distributions, based on Type-I censoring. We derive Bayes estimators with a variety of loss functions, including symmetric Squared Error, asymmetric Linear Exponential, and General Entropy, utilizing both informative and noninformative priors. We also go over how to create the model's two-sample Bayesian prediction intervals. To demonstrate these methods, we provide computational results through Monte Carlo simulations and real data. | ||||
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