Statistical inference for function-on-function linear regression

We propose a reproducing kernel Hilbert space approach to estimate the slope in a function-on-function linear regression via penalised least squares, regularized by the thin-plate spline smoothness penalty. In contrast to most of the work on functional linear regression, our main focus is on statist... View More