Estimation for Inverse Weibull Distribution Under Type-I Hybrid Censoring

The mixture of Type I and Type II censoring schemes is called the hybrid censoring. This paper presents the statistical inferences of the Inverse Weibull distribution when the data are Type-I hybrid censored. First we consider the maximum likelihood estimators of the unknown parameters. It is observed that the maximum likelihood estimators can not be obtained in closed form. We further obtain the Bayes estimators and the corresponding highest posterior density credible intervals of the unknown parameters under the assumption of independent gamma priors using the importance sampling procedure. We also compute the approximate Bayes estimators using Lindley's approximation technique. We have performed a simulation study in order to compare the proposed Bayes estimators with the maximum likelihood estimators. A real life data set is used to illustrate the results derived.