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Statistical Inference of Concomitants Based on Morgenstern Family under Generalized Order Statistics |
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PP: 243-254 |
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doi:10.18576/msl/050305
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Author(s) |
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M. M. Mohie El-Din,
Nahed S. A. Ali,
M. M. Amein,
M. S. Mohamed,
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Abstract |
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| In this paper, the joint densities of the concomitants of generalized order statistics (GOS’s) for exponential and power
function subfamilies of Morgenstern family are derived. Statistical inference such as maximum likelihood (ML) and Bayesian
estimation under different types of loss functions based on informative and non-informative priors for the distribution parameters,
reliability and cumulative hazard functions are obtained. In addition, Bayesian prediction bounds, Bayes predictive estimator and
approximate confidence intervals of the estimators are considered. Applications of these results are given for concomitants of order
statistics are presented. |
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