# predict.bagEarth: Predicted values based on bagged Earth and FDA models

## Description

Predicted values based on bagged Earth and FDA models

## Usage

# S3 method for bagEarth
predict(object, newdata = NULL, type = NULL, ...)# S3 method for bagFDA
predict(object, newdata = NULL, type = "class", ...)

## Arguments

object

Object of class inheriting from `bagEarth`

newdata

An optional data frame or matrix in which to look for
variables with which to predict. If omitted, the fitted values are used
(see note below).

type

The type of prediction. For bagged `earth`

regression model, `type = "response"`

will produce a numeric vector of
the usual model predictions. `earth`

also allows the user
to fit generalized linear models. In this case, `type = "response"`

produces the inverse link results as a vector. In the case of a binomial
generalized linear model, `type = "response"`

produces a vector of
probabilities, `type = "class"`

generates a factor vector and
`type = "prob"`

produces a two-column matrix with probabilities for
both classes (averaged across the individual models). Similarly, for bagged
`fda`

models, `type = "class"`

generates a factor
vector and `type = "probs"`

outputs a matrix of class probabilities.

## Value

A vector of predictions (for regression or `type = "class"`

)
or a data frame of class probabilities. By default, when the model
predicts a number, a vector of numeric predictions is returned. When
a classification model is used, the default prediction is a factor vector
of classes.

## Examples

# NOT RUN {
# }
# NOT RUN {
data(trees)
## out of bag predictions vs just re-predicting the training set
set.seed(655)
fit1 <- bagEarth(Volume ~ ., data = trees, keepX = TRUE)
set.seed(655)
fit2 <- bagEarth(Volume ~ ., data = trees, keepX = FALSE)
hist(predict(fit1) - predict(fit2))
# }
# NOT RUN {
# }