Generalized Additive Models

Abstract Generalized additive models replace the linear predictor in a linear model or generalized linear model framework with an additive predictor composed of nonparametric or semiparametric functions of the explanatory variables. Similarly to generalized linear models, the predictor is linear in the link function of the response mean, and the response variable can have a non normal distribution. The last decade has seen interesting new approaches to estimation of generalized additive models, and the development of a mixed effects framework for these models.