ON THE CONVERGENCE OF RECURSIVE KERNEL DENSITY ESTIMATORS FOR WIDELY ORTHANT DEPENDENT AND CENSORED DATA

In this article, we establish the almost sure convergence of a family of recursive estimators when the data are censored checking widely orthant dependence (WOD). The dependence hypothesis gives this work a certain originality because most often, the study of censored data is done with an independence hypothesis and in reality the real data are often dependent.