Non Parametric Estimation of the Family of Risk Measures Based onProgressive Type II Censored Data

In this paper, some methods of estimation for the class of variability measures among proportional hazards models based on progressively Type-II censored data are derived. Simulation studies have been performed to see the effectiveness of the proposed methods, and a real data set has been analyzed for illustrative purposes. Some well-known variability measures, such as the Gini mean difference, the Wang right tail deviation and the cumulative residual entropy are, up to a scale factor, in this class.