Hilbertian additive regression with parametric help.

We discuss a way of improving local linear additive regression when the response variable takes values in a general separable Hilbert space. Our methodology covers the case of non-additive regression function as well as additive. We present relevant theory in this flexible framework and demonstrate the benefits of the proposed technique via a real data application. [ABSTRACT FROM AUTHOR]