  We consider the problem of the construction of the estimator-process of the
unknown finite-dimensional parameter in the case of the observations of
nonlinear autoregressive process. The estimation is done in two or three steps.
First we estimate the unknown parameter by a learning relatively short part of
observations and then we use the one-step MLE idea to construct an-estimator
process which is asymptotically equivalent to the MLE. To have the learning
interval shorter we introduce the two-step procedure which leads to the
asymptotically efficient estimator-process too. The presented results are
illustrated with the help of two numerical examples.
