RによるGAM入門

抄録

This article presents an introduction to generalized additive models using R for data of mutually exclusive groups 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. The cross-validation is also adapted for influential analysis in order to verify the appropriateness of the model and to detect observations that do not agree with the rest of the data.