Maximum Product Spacing and Bayesian Method for Parameter Estimation for Generalized Power Weibull Distribution Under Censoring Scheme

This article discusses the estimation of Generalized Power Weibull parameters using maximum product spacing (MPS) method, likelihood (ML) method and Bayesian under squares error for loss function. The is done progressive type-II censored samples a comparative study among three methods made Monte Carlo Simulation. Markov chain (MCMC) has been employed to compute Bayes estimators distribution. optimal censoring scheme suggested two different optimality criteria (mean squared error, Bias relative efficiency). A real data used performance process this in practice illustrative purposes. Finally, we discuss obtaining scheme.