Bayesian Estimation for the Parameters of the WEM Based on GOS - Nassar, Mazen;Abu Elfotouh, Samia
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In this work, the estimation problem for the unknown parameters of Weibull extension model (WEM) is investigated based on generalized order statistics. Maximum likelihood estimators and their asymptotic variance-covariance matrix are derived, also Bayes estimators using symmetric squared error loss function are obtained using non-informative type of priors for the parameters. Some numerical results using simulation study are reported.

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Produktbeschreibung
In this work, the estimation problem for the unknown parameters of Weibull extension model (WEM) is investigated based on generalized order statistics. Maximum likelihood estimators and their asymptotic variance-covariance matrix are derived, also Bayes estimators using symmetric squared error loss function are obtained using non-informative type of priors for the parameters. Some numerical results using simulation study are reported.
Autorenporträt
Mazen Nassar is an assistant teacher of statistics in the department of statistic, faculty of commerce, Zagazig University, Zagazig, Egypt. He received his B.Sc., and M.Sc. degrees in statistics from Zagazig University, in 2006, and 2011, respectively. He is a PhD student at the institute of statistical studies and research, Cairo university, Egypt.