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

Ehab Mohamed Almetwally, Hisham Mohamed Almongy, Amaal El sayed Mubarak

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.


Keywords


Weibull Generalized Exponential Distribution, Maximum Likelihood Estimation, Bayesian Estimation, MCMC, Censoring Scheme

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DOI: http://dx.doi.org/10.18187/pjsor.v14i4.2600

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Title

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

Keywords

Weibull Generalized Exponential Distribution, Maximum Likelihood Estimation, Bayesian Estimation, MCMC, Censoring Scheme

Description

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.


Date

2018-12-25

Identifier


Source

Pakistan Journal of Statistics and Operation Research; Vol. 14 No. 4, 2018



Print ISSN: 1816-2711 | Electronic ISSN: 2220-5810