Nonparametric estimation of bivariate additive models

In this paper we discuss the estimation of a bivariate additive model where the multivariate regression function is expressed as a sum of unknown univariate and bivariate component functions. We discuss the identifiability of the component functions and show that each component function of the model can be estimated at the optimal rate in bivariate kernel smoothing.