  We constuct a sequential adaptive procedure for estimating the autoregressive
function at a given point in nonparametric autoregression models with Gaussian
noise. We make use of the sequential kernel estimators. The optimal adaptive
convergence rate is given as well as the upper bound for the minimax risk.
