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Bayesian Estimation and Prediction of the Rayleigh Distribution Based on Ordered Ranked Set Sampling under Type-II Doubly Censored Samples |
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PP: 83-95 |
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doi:10.18576/jsapl/080202
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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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| A ranked set sampling (RSS) scheme is an efficient and cost-effective alternative to simple random sampling when the sampling units can be ranked visually or by any inexpensive method. In this study, we first use ordered ranked set sampling (ORSS) in obtaining Bayesian estimation for the parameter of the Rayleigh distribution under Type-II doubly censoring scheme. This is done with respect to both squared error loss and Al-Bayyati loss functions. We obtain the mean squared error (MSE) and bias of the derived estimates based on m-cycle ORSS and compare them with those based on the corresponding simple random sample (SRS) to appreciate the efficiency of the obtained estimators. Next, we present the two-sample Bayesian predictive density function (point and interval) for the s-th ordered lifetime from a future independent sample. Finally, simulation study and real data are analyzed for illustrative purpose.
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