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.

14 pages, 1 figure, 6 tables

References in corpus (2)

• Single and multiple index functional regression models with nonparametric link
• Automatic and location-adaptive estimation in functional single-index regression