Bayesian and Maximum Likelihood Estimations of the Inverse Weibull Parameters Under Progressive Type-II Censoring

In this paper, the statistical inference of the unknown parameters of a twoparameter inverse Weibull (IW) distribution based on the progressive Type-II censored sample has been considered. The maximum likelihood estimators cannot be obtained in explicit forms, hence the approximate maximum likelihood estimators are proposed, which are in explicit forms. The Bayes and generalized Bayes estimators for the IW parameters and the reliability function based on the squared error and Linex loss functions are provided. The Bayes and generalized Bayes estimators cannot be obtained explicitly, hence Lindley’s approximation is used to obtain the Bayes and generalized Bayes estimators. Further the highest posterior density credible intervals of the unknown parameters based on Gibbs sampling technique are computed, and using an optimality ∗Corresponding author: E-mail : [email protected]