Sonja Greven, Amanda Fernández-Fontelo, Felix Henninger, Pascal J. Kieslich, Frauke Kreuter
An ensemble method for multivariate functional data classification, with application to mouse movement trajectories

An ensemble method is presented for multivariate functional data classification that combines different semi-metric-based classifiers. We extend existing methods to the multivariate case and to further ensemble methods, and allow for scalar covariates. An R package implements the presented classification methods for multivariate functional data and trajectories in n dimensions. We apply our methods to the motivating application, to predict the difficulty of respondents while filling out a web survey using their computer mouse trajectories.