Asymptotically efficient estimates for nonparametric regression models

The paper deals with estimating problem of regression function at a given state point in nonparametric regression models with Gaussian noises and with non-Gaussian noises having unknown distribution. An asymptotically efficient kernel estimator is constructed for a minimax risk.