Cumulative Residual Extropy for Pareto Distribution in the Presence of Outliers: Bayesian and Non-Bayesian Methods

The extropy is considered to be a complementary dual of the well-known Shannon’s entropy and has wide applications in many fields. This article discusses estimating cumulative residual Pareto distribution using maximum likelihood Bayesian methods. We obtain extropies measures presence outliers. These estimators are specialized homogenous case. both derived based on symmetric asymmetric loss functions. Markov chain Monte Carlo methods used accomplish some complex calculations. precision estimates for examined through simulations. Regarding results simulation study, we conclude that performances estimation improve with sample sizes. Also, under linear exponential function superior other functions most cases. performance increase number outliers almost Generally, there great agreement between theoretical empirical results. Further comparison conducted by experiments real data.