Generalized Additive Models

Generalized Additive Models combine the notion of additive models with generalized linear/nonlinear models to derive the notion of generalized additive models.

In other words, the purpose of generalized additive models is to maximize the quality of prediction of a dependent variable Y from various distributions by estimating unspecific (nonparametric) functions of the predictor variables that are "connected" to the dependent variable via a link function.