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Bayesian and Maximum Likelihood Estimation for the Weibull Generalized Exponential Distribution Parameters Using Progressive Censoring Schemes

Author(s)
Ehab Mohamed Almetwally Institute of Statistical Studies and Research, Cairo Statistics, Egypt
Amaal El sayed Mubarak Department of Applied Statistics, Faculty of Commerce - Damietta University, Egypt
Hisham Mohamed Almongy Department of Applied Statistics, Faculty of Commerce - Mansoura University, Egypt
Abstract
In this paper we consider the estimation of the Weibull Generalized Exponential Distribution (WGED) Parameters with Progressive Censoring Schemes. In order to obtain the optimal censoring scheme for WGED, more than one method of estimation was used to reach a better scheme with the best method of estimation. The maximum likelihood method and the method of Bayesian estimation for (square error and Linex) loss function have been used. Monte carlo simulation is used for comparison between the two methods of estimation under censoring schemes. To show how the schemes work in practice; we analyze a strength data for single carbon fibers as a case of real data.
Publication Details
Page(s) 853-868
DOI DOI not available
Published Journal: Pakistan Journal of Statistics and Operation Research, Volume: 14, Issue: 4, Year: 2018

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Keywords
Bayesian estimation, MCMC, Estimation, Weibull generalized exponential distribution, Censoring scheme
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