Efficient estimation of the error distribution function in heteroskedastic nonparametric regression with missing data

Abstract: A residual-based empirical distribution function is proposed to estimate the distribution function of the errors of a heteroskedastic nonparametric regression with responses missing at random based on completely observed data, and this estimator is shown to be asymptotically most precise.