Bias reduction in functional estimation

New kernel distribution function and kernel density function estimators based on a nonparametric transformation of the data for the purpose of bias reduction are proposed. Asymptotic bias expansions for the new estimators are presented and analyzed. Statistical properties in terms of bias, variance, and mean squared error of the new estimators are investigated with computer simulations.