Multiple Functional Regression with both Discrete and Continuous Covariates

Abstract

In this paper we present a nonparametric method for extending functional\nregression methodology to the situation where more than one functional\ncovariate is used to predict a functional response. Borrowing the idea from\nKadri et al. (2010a), the method, which support mixed discrete and continuous\nexplanatory variables, is based on estimating a function-valued function in\nreproducing kernel Hilbert spaces by virtue of positive operator-valued\nkernels.\n