Non-parametric estimation of the residual distribution

Abstract

Consider a heteroscedastic regression model Y = m(X) + sigma (X)epsilon, where the functions m and sigma are "smooth", and epsilon is independent of X. An estimator of the distribution of epsilon based on non-parametric regression residuals is proposed and its weak convergence is obtained. Applications to prediction intervals and goodness-of-fit tests are discussed.