Cross-validated local linear nonparametric regression

Local linear kernel methods have been shown to dominate local constant methods for the nonparametric estimation of regression functions. In this paper we study the theoretical properties of cross-validated smoothing parameter selection for the local linear kernel estimator. We derive the rate of convergence of the cross-validated smoothing parameters to their optimal benchmark values, and we establish the asymptotic normality of the resulting …