Recursive estimation of nonparametric regression with functional   covariate
  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. 
Aboubacar Amiri (EQUIPPE), Christophe Crambes (I3M), Baba Thiam   (EQUIPPE)
math.ST stat.TH