Bayesian Estimators of Dynamic Cumulative Residual Entropy for Pareto Type II Distribution using Asymmetric Loss Function

Abstract

In this paper, Pareto Type II distribution is used to propose the Bayesian estimators of DCRE (Dynamic Cumulative residual entropy). To calculate posterior risks various informative and non-informative priors are used. Using different asymmetric loss functions (GELF, ELF, KLF and PLF), Bayes estimators and associated posterior risks for this distribution have been calculated. Numerical computation is done with the help of a real data set. In the last, Monte carlo Simulation study and graphical analysis are also given alongwith the conclusion drawn.