B0843
Title: Combining concurrent and historical functional linear regression
Authors: Dominik Liebl - University Bonn (Germany) [presenting]
Sven Otto - University of Cologne (Germany)
Alois Kneip - University of Bonn (Germany)
Abstract: A new function-on-function linear regression model that incorporates common and point effects of a regressor function on a response function is introduced. The model comprises two components: a Hilbert-Schmidt integral operator for the common component and a concurrent component that captures the regressor's impact on the response at each domain point. The identification of the model is discussed, proposing a smoothing spline estimator, providing asymptotic theory, and demonstrating its practicality using sports data.
