On kernel distribution function estimation near end points

Abstract

Under that so-called boundary problem on kernel cumulative distribution function estimation, the main objective of this paper is to introduce and investigate the properties of our new estimator in order to improve the boundary effects, we will restrict our attention to the right boundary. We turned out that the order of the Bias has been reduced to the second power of the bandwidth, simulation studies for three different types of bandwidth selecting methods were carried out to check these phenomena, we conclude that the proposed estimator is better than the existing boundary correction methods.