Communications in Statistics - Theory and Methods, ( ISI ), Volume (41), No (8), Year (2012-3) , Pages (1334-1349)

Title : ( Central Limit Theorem for ISE of Kernel Density Estimators in Censored Dependent Model )

Authors: Sara Jomhoori , Vahid Fakoor , Hassan Ali Azarnoosh ,

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Abstract

In some long-term studies, a series of dependent and possibly censored failure times may be observed. Suppose that the failure times have a common continuous distribution function F. A popular stochastic measure of the distance between the density function f of the failure times and its kernel estimate fn is the integrated square error(ISE). In this article, we derive a central limit theorem for the integrated square error of the kernel density estimators under a censored dependent model.

Keywords

, , mixing; Bandwidth; Censored dependent data; Integrated square error; Kaplan–Meier estimator; Kernel density estimator.