In hofnerb/mboost: Model-Based Boosting

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")

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))

which can be compared to the actual response values:

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

hofnerb/mboost documentation built on Jan. 10, 2024, 9:21 p.m.