GAM and Its Related Problems

Abstract

This article presents generalized additive models using penalized smoothing for binary response data and a set of predictor variables. Illustrated herein are a number of resampling methods, that is cross-validation when selecting the optimum smoothing parameter, and bootstrapping applications that implement the bootstrap-based information when using the deviance in order to summarize the measure of goodness-of-fit on generalized additive models.