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Bayesian Estimation and Prediction for Inverse Weibull Distribution under Generalized Order Statistics |
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PP: 9-17 |
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doi:10.18576/jsapl/090102
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Author(s) |
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Mostafa M. Mohie El-Din,
Mohamed S. Kotb,
Haidy A. Newer,
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Abstract |
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| This paper deals with the problem of Bayesian prediction for a past ordered observations when the r ordered observations remaining drawn from inverse Weibull (IW) distribution based on dual generalized order statistics. The predictive survival function in the one sample case can not be obtained in closed form, so Markov Chain Monte Carlo (MCMC) samples used to compute the approximate predictive survival function. Estimation for the two parameters, reliability and hazard functions of the IW distribution are obtained in two cases: squared error loss (SEL) and asymmetric loss functions (LINEX). A real data set and simulation data are used to illustrate the theoretical results.
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