Moments and estimation of reduced Kies distribution based on progressive type-II right censored order statistics

Abstract

Based on progressive type-II censored samples, we rst derive the re- currence relations for the single and product moments and then use these results to compute the means and variances of reduced Kies dis- tribution (RKD), a new distribution, recently introduced by [21]. Next, we obtain the maximum likelihood estimators of the unknown param- eter and the approximate con dence interval of the RKD. Finally, we consider Bayes estimation under the symmetric and asymmetric loss functions using gamma prior for the shape parameter. We have also derived two-sided Bayes probability interval (TBPI) and the highest posterior density (HPD) credible intervals of this distribution. Monte Carlo simulations are performed to compare the performances of the proposed methods, and a data set has been analyzed for illustrative purposes.