Stable and Efficient Multiple Smoothing Parameter Estimation for Generalized Additive Models
广义加性模型中稳定高效的多重平滑参数估计
Representation of generalized additive models (GAM's) using penalized regression splines allows GAM's to be employed in a straightforward manner using penalized regression methods. Not only is inference facilitated by this approach, but it is also possible to integrate model selection in the form of smoothing parameter selection into model fitting in a computationally efficient manner using well founded criteria such as generalized cross-validation. The current fitting and…