A $k$NN procedure in semiparametric functional data analysis

Abstract

A fast and flexible $k$-NN procedure is developed for dealing with a semiparametric functional regression model involving both partial-linear and single-index components. Rates of uniform consistency are presented. Simulated experiments highlight the advantages of the $k$-NN procedure. A real data analysis is also shown.