Nonparametric -Divergence Estimation and Test for Model Selection

Abstract

In this paper, we study a bias reduced kernel density estimator and derive a nonparametric -divergence estimator based on this density estimator. We investigate the asymptotic properties of these two estimators and we formulate an asymptotically standard normal test for model selection.