A bagging wrapper for multivariate adaptive regression
splines (MARS) via the earth function
Usage
bagEarth(x, ...)
# S3 method for default
bagEarth(x, y, weights = NULL, B = 50,
summary = mean, keepX = TRUE, ...)
# S3 method for formula
bagEarth(formula, data = NULL, B = 50,
summary = mean, keepX = TRUE, ..., subset, weights = NULL,
na.action = na.omit)
# S3 method for bagEarth
print(x, ...)
Arguments
x
matrix or data frame of 'x' values for examples.
…
arguments passed to the earth function
y
matrix or data frame of numeric values outcomes.
weights
(case) weights for each example - if missing defaults to 1.
B
the number 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?
formula
A formula of the form y ~ x1 + x2 + ...
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. (NOTE: If
given, this argument must be named.)
Value
A list with elements
fit
a list of B Earth fits
B
the number of bootstrap samples
call
the function call
x
either NULL or the value of x, depending on the
value of keepX
oob
a 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.
# NOT RUN {library(mda)
library(earth)
data(trees)
fit1 <- earth(x = trees[,-3], y = trees[,3])
set.seed(2189)
fit2 <- bagEarth(x = trees[,-3], y = trees[,3], B = 10)
# }# NOT RUN {# }