Kernel Estimation of The Dynamic Cumulative Past Inaccuracy Measure for Right Censored Dependent Data

Accepted - December 2022

Abstract

This paper proposes a nonparametric estimator for the lifetime distribution’s dynamic cumulative past inaccuracy measure based on censored dependent data. The asymptotic properties of the estimator are discussed under suitable regularity conditions. We use Monte-Carlo simulations to compare the estimator’s performance to that of an empirical estimator using mean squared errors to test the estimator’s properties numerically. The methods are demonstrated using two different real data sets.