Estimation of entropy and extropy based on right censored data: A Bayesian non-parametric approach
Luai Al‐Labadi, Muhammad Tahir · Monte Carlo Methods and Applications · 2022
Abstract Entropy and extropy are central measures in information theory. In this paper, Bayesian non-parametric estimators to entropy and extropy with possibly right censored data are proposed. The approach uses the beta-Stacy process and the difference operator. Examples are presented to illustrate the performance of the estimators.