# Getting Started

# Your first boosted model

First, install and fire-up R on your computer. Within R, one needs to install the mboost package by typing

```
install.packages("mboost")
```

and hitting the ENTER key. Once the package is installed, you can load it using

```
library("mboost")
```

```
## Loading required package: parallel
```

```
## Loading required package: stabs
```

```
## This is mboost 2.8-1. See 'package?mboost' and 'news(package = "mboost")'
## for a complete list of changes.
```

Now all mboost functions are ready to be used, for example the mboost() function for fitting an additive regression model to the bodyfat data

```
data("bodyfat", package = "TH.data")
### formula interface: additive Gaussian model with
### a non-linear step-function in `age', a linear function in `waistcirc'
### and a smooth non-linear smooth function in `hipcirc'
mod <- mboost(DEXfat ~ btree(age) + bols(waistcirc) + bbs(hipcirc),
data = bodyfat)
```

The model can be plotted

```
layout(matrix(1:3, nc = 3, byrow = TRUE))
plot(mod, ask = FALSE, main = "formula")
```

or used for computing predictions

```
summary(predict(mod))
```

```
## V1
## Min. :13.35
## 1st Qu.:22.61
## Median :29.50
## Mean :30.78
## 3rd Qu.:38.41
## Max. :50.15
```

which can be compared to the actual response values:

```
plot(bodyfat$DEXfat, predict(mod))
abline(a = 0, b = 1)
```