In this paper, we compared between the maximum likelihood estimator (MLE) and Bayesian estimation for the shape parameters and of the generalized power Weibull (GPW) distribution based on complete censoring data, type-II censoring scheme and type-II progressive censoring scheme. The Bayesian estimates for the GPW parameters are obtained based on binary loss function and squared error loss function. The optimal censoring scheme has been suggested using two different optimality criteria (mean squared of error (MSE) and Bias). This comparison was done by using simulation study and application on real life of data. We discussed the method of obtaining the optimal type-II progressive censoring schemes.
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