# Model-based boosting in R: a hands-on tutorial using the R package **mboost**

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## Abstract

We provide a detailed hands-on tutorial for the R add-on package **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 **mboost** can be used to fit interpretable models of different complexity. As an example we use **mboost** to predict the body fat based on anthropometric measurements throughout the tutorial.

## Keywords

Boosting Component-wise functional gradient descent Generalized additive models Tutorial## Notes

### Acknowledgments

The authors thank two anonymous referees for their comments that helped to improve this article.

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© Springer-Verlag Berlin Heidelberg 2012