Law of the Iterated Logarithm for Non-Parametric Regression Function Estimators.

摘要

We prove a law of the iterated logarithm for nonparametric regression function estimators using strong approximations to the two dimensional empirical process. We consider the case of Nadaraya-Watson kernel estimators and of estimators based on orthogonal polynomials when the marginal density of the design variable X is unknown or known. (Author)