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Research Article Open access CC BY 4.0

Bayesian Prediction for Exponentiated Generalized Xgamma Distribution Based on Dual Generalized Order Statistics with Application to Poverty and COVID-19 Mortality Rates

R. E. Abd El-Kader, A. M. Abd Al-Fattah, G. R. AL-Dayian, A. A. EL-Helbawy

Journal of Advances in Mathematics and Computer Science · pp. 30–53 · Published 10 May 2021

10.9734/jamcs/2021/v36i430355

Abstract

Statistical prediction is one of the most important problems in life testing; it has been applied in medicine, engineering, business and other areas as well. In this paper, the exponentiated generalized xgamma distribution is introduced as an application on the exponentiated generalized general class of distributions. Bayesian point and interval prediction of exponentiated generalized xgamma distribution based on dual generalized order statistics are considered. All results are specialized to lower records. The results are verified using simulation study as well as applications to real data sets to demonstrate the flexibility and potential applications of the distribution.

Exponentiated generalized distributions bayesian prediction dual generalized order statistics exponentiated generalized xgamma distribution

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