• BAYESIAN AND CLASSICAL ESTIMATION FOR THE WEIBULL DISTRIBUTION PARAMETERS UNDER PROGRESSIVE TYPE-II CENSORING SCHEMES

Abstract

This article discusses the estimation of the Weibull parameters using the maximum product spacing (MPS), the maximum likelihood (ML) and Bayesian estimation methods. The estimation is done under progressive type-II censored samples and a comparative study among the three methods is made using Monte Carlo Simulation. A real data is used to study the performance of the estimation process under this optimal scheme in practice. We also discuss the construction of progressively censored sampling plans for the Weibull distribution to determine the optimal progressive censoring plans. Lindley’s approximation has been employed to compute the Bayes estimators of the Weibull distribution.