Classification of functional data: a weighted distance approach

Abstract

A popular approach for classifying functional data is based on the distances from the function or its derivatives to group representative (usually the mean) functions or their derivatives. In this paper, we propose using a combination of those distances. Simulation studies show that our procedure performs very well, resulting in smaller testing classication errors. Applications to real data show that our procedure performs as well as –and in some cases better than– other classication methods.