Smoothing Parameter Selection for a Class of Semiparametric Linear Models
Smoothing Parameter Selection for a Class of Semiparametric Linear Models
Summary Spline-based approaches to non-parametric and semiparametric regression, as well as to regression of scalar outcomes on functional predictors, entail choosing a parameter controlling the extent to which roughness of the fitted function is penalized. We demonstrate that the equations determining two popular methods for smoothing parameter selection, generalized cross-validation …