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

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.   :13.45  
##  1st Qu.:22.65  
##  Median :29.48  
##  Mean   :30.78  
##  3rd Qu.:38.45  
##  Max.   :50.08

which can be compared to the actual response values:

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