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Bayesian and Classical Inference for Power-Modified Kies-Exponential Distribution |
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PP: 569-584 |
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doi:10.18576/jsap/140406
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Author(s) |
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F. N. Fouad,
M. M. Nassar,
S. E. Abu-Youssef,
R. M. EL-Sagheer,
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Abstract |
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| This study aims to estimate the parameters of the power-modified Kies-exponential distribution and various lifetime measures, including reliability and hazard rate functions, under progressive type-II censoring. It investigates the application of maximum likelihood estimation, two-parametric bootstrap, and Bayesian approaches to derive these parameters and characteristics. Approximate confidence intervals and highest posterior density credible intervals are constructed using the asymptotic properties of maximum likelihood estimators and the Markov chain Monte Carlo method, respectively. Furthermore, the delta method is utilized to compute variances for reliability and hazard functions, while two bootstrap techniques are employed for confidence interval estimation. Bayesian inference is developed based on squared error loss functions. Lastly, comprehensive simulation studies are carried out to evaluate the effectiveness of these estimation techniques, and a real data analysis is performed to illustrate their practical applicability.
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