  In this paper we propose an automatic selection of the bandwidth of the
semi-recursive kernel estimators of a regression function defined by the
stochastic approximation algorithm. We showed that, using the selected
bandwidth and some special stepsizes, the proposed semi-recursive estimators
will be very competitive to the nonrecursive one in terms of estimation error
but much better in terms of computational costs. We corroborated these
theoretical results through simulation study and a real dataset.
