Model-based boosting in R: a hands-on tutorial using the R package <Emphasis Type="Bold">mboost

We provide a detailed hands-on tutorial for the R add-on package <Emphasis Type="Bold">mboost. The package implements boosting for optimizing general risk functions utilizing component-wise (penalized) least squares estimates as base-learners for fitting various kinds of generalized linear and generalized additive models to potentially high-dimensional data. We give a theoretical background and demonstrate how <Emphasis Type="Bold">mboost can be used to fit interpretable models of different complexity. As an example we use <Emphasis Type="Bold">mboost to predict the body fat based on anthropometric measurements throughout the tutorial. Copyright Springer-Verlag Berlin Heidelberg 2014