Kernel Estimation of Entropy Function for Length-Biased Censored Data

Abstract

In this article, we propose nonparametric kernel type estimators for the Shannon differential entropy for length-biased censored data. The asymptotic properties of the estimators are established under specific regularity conditions. The performance of the estimators is examined through simulated observations and is compared using mean squared errors for various sample sizes. The applicability of the estimators is demonstrated using real data.