Higher order bias reduction of kernel density and density derivative estimation at boundary points

Abstract

A new, direct method is developed for reducing, to an arbitrary order, the boundary bias of kernel density and density derivative estimators. The basic asymptotic properties of the estimators are derived. Simple examples are provided. A number of simulations are reported, which demonstrate the viability and efficacy of the approach compared to several popular alternatives.

Citation

Bearse, P. and Rilstone, P. (2009), "Higher order bias reduction of kernel density and density derivative estimation at boundary points", Li, Q. and Racine, J.S. (Ed.) Nonparametric Econometric Methods (Advances in Econometrics, Vol. 25), Emerald Group Publishing Limited, Leeds, pp. 319-331. https://doi.org/10.1108/S0731-9053(2009)0000025013