## Description

A bagging wrapper for multivariate adaptive regression
splines (MARS) via the `earth`

function## Usage

## S3 method for class 'formula':
bagEarth(formula, data = NULL, B = 50,
summary = mean, keepX = TRUE,
..., subset, weights, na.action = na.omit)
## S3 method for class 'default':
bagEarth(x, y, weights = NULL, B = 50,
summary = mean, keepX = TRUE, ...)

## Arguments

formula

A formula of the form `y ~ x1 + x2 + ...`

x

matrix or data frame of 'x' values for examples.

y

matrix or data frame of numeric values outcomes.

weights

(case) weights for each example - if missing defaults to 1.

data

Data frame from which variables specified in 'formula' are
preferentially to be taken.

subset

An index vector specifying the cases to be used in the
training sample. (NOTE: If given, this argument must be
named.)

na.action

A function to specify the action to be taken if 'NA's are
found. The default action is for the procedure to fail. An
alternative is na.omit, which leads to rejection of cases
with missing values on any required variable. (N

B

the numebr of bootstrap samples

summary

a function with a single argument specifying how the bagged predictions should be summarized

keepX

a logical: should the original training data be kept?

...

arguments passed to the `earth`

function

## Value

- A list with elements
- fita list of
`B`

Earth fits - Bthe number of bootstrap samples
- callthe function call
- xeither
`NULL`

or the value of `x`

, depending on the
value of `keepX`

- ooba matrix of performance estimates for each bootstrap sample

## Details

The function computes a Earth model for each bootstap sample.## References

J. Friedman, ``Multivariate Adaptive Regression Splines'' (with
discussion) (1991). Annals of Statistics, 19/1, 1-141.## Examples

library(mda)
library(earth)
data(trees)
fit1 <- earth(trees[,-3], trees[,3])
fit2 <- bagEarth(trees[,-3], trees[,3], B = 10)