Estimation for the half-logistic distribution based on multiply Type-II hybrid censoring

Abstract

In this paper, some estimators of the scale parameter of the half-logistic distribution are derived under the multiply Type-II hybrid censoring scheme. We propose three methods. First, we obtain the maximum likelihood estimator of the scale parameter of the half-logistic distribution. Second, we propose some approximate maximum likelihood estimators of the scale parameter by employing three different types of Taylor series expansions. Lastly, we obtain the Bayes estimators by employing some prior distributions and loss functions. The interval estimations such as the asymptotic confidence interval and the credible interval and the highest posterior density interval are obtained. To assess the performance of the proposed estimators, we obtain the mean squared error, average length of 95% interval and coverage probability through Monte Carlo simulation and applies to the real dataset.