Statistical inference of for Weibull distribution under Type II progressively hybrid censored data
ABSTRACT Type II progressively hybrid censoring is a mixture of Type II progressive and hybrid censoring schemes. In this paper, we consider the estimation of when X and Y are two independent Weibull distributions with different scale parameters, but having the same shape parameter, and the data obtained from both distributions are Type II progressively hybrid censored. Different methods for estimating are applied. The maximum likelihood estimator and the approximate maximum likelihood estimator of are proposed. The observed Fisher information matrix is computed and it is used to construct an asymptotic confidence interval for Also, two bootstrap confidence intervals are proposed. Bayes estimate of and the associated credible interval are also obtained under the assumption of independent suitable priors. Monte Carlo simulations are performed to compare the efficiency of the proposed estimators. One data analysis has been presented for illustrative purposes.