Estimation Based on Progressively Censored Data from the Burr Model

Abstract

Based on progressively Type-II censored samples, the uniformly min-imum variance unbiased (UMVU), Bayes and empirical Bayes estimates for the unknown parameter and the reliability function of the Burr model are derived. The Bayes and empirical Bayes estimates are ob-tained based on absolute error and logarithmic loss functions. We also present a numerical example and a Monte Carlo simulation study to illustrate the results.