  The main purpose is to estimate the regression function of a real random
variable with functional explanatory variable by using a recursive
nonparametric kernel approach. The mean square error and the almost sure
convergence of a family of recursive kernel estimates of the regression
function are derived. These results are established with rates and precise
evaluation of the constant terms. Also, a central limit theorem for this class
of estimators is established. The method is evaluated on simulations and real
data set studies.
