earth (version 4.1.0)

predict.earth: Predict with an earth model

Description

Predict with an earth model.

Usage

## S3 method for class 'earth':
predict(object = stop("no 'object' arg"), newdata = NULL,
        type = c("link", "response", "earth", "class", "terms"),
        interval = "none", level = .95,
        thresh = .5, trace = FALSE, ...)

Arguments

object

An earth object. This is the only required argument.

newdata

Make predictions using newdata, which can be a data frame, a matrix, or a vector with length equal to a multiple of the number of columns of the original input matrix x. Note that this is more flexible than the predic

type

Type of prediction. One of "link" (default), "response", "earth", "class", or "terms". See the Note below.

interval

Return prediction or confidence levels. Default is "none". Use interval="pint" to get prediction intervals on new data. Requires that the earth model was built with varmod.method. This argument gets passed

level

Confidence level for the interval argument. Default is .95, meaning construct 95% confidence bands (assume the residual variance is symmetrical and calculate 2.5% and 97.5% levels).

thresh

Threshold, a value between 0 and 1 when predicting a probability. Only applies when type="class". Default is .5. See the Note below.

trace

Default FALSE. Set to TRUE to see which data, subset, etc. predict.earth is using.

...

Unused, but provided for generic/method consistency.

Value

• The predicted values (a matrix for multiple response models).

  If type="terms", a matrix with each column showing the contribution of a predictor.

  If interval="pint", "training.cint", or "training.pint", a matrix with three columns: fit: the predicted values lwr: the lower confidence or prediction limit upr: the upper confidence or prediction limit

  If interval="se", the standard errors.

See Also

earth, predict

Examples

data(trees)
earth.mod <- earth(Volume ~ ., data = trees)
predict(earth.mod)           # same as earth.mod$fitted.values
predict(earth.mod, c(10,80)) # yields 16.8