elasticnet (version 1.02)

predict.enet: Make predictions or extract coefficients from a fitted elastic net model

Description

While enet() produces the entire path of solutions, predict.enet allows one to extract a prediction at a particular point along the path.

Usage

predict.enet(object, newx, s, type = c("fit", "coefficients"), mode =
c("step","fraction", "norm", "penalty"),naive=FALSE, ...)

Arguments

object

A fitted enet object

newx

If type="fit", then newx should be the x values at which the fit is required. If type="coefficients", then newx can be omitted.

s

a value, or vector of values, indexing the path. Its values depends on the mode= argument. By default (mode="step").

type

If type="fit", predict returns the fitted values. If type="coefficients", predict returns the coefficients. Abbreviations allowed.

mode

Mode="step" means the s= argument indexes the LARS-EN step number, and the coefficients will be returned corresponding to the values corresponding to step s. If mode="fraction", then s should be a number between 0 and 1, and it refers to the ratio of the

naive

IF naive is True, then the naive elastic net fit is returned.

...

Additonal arguments for generic print.

Value

• Either a vector/matrix of fitted values, or a vector/matrix of coefficients.

Details

Starting from zero, the LARS-EN algorithm provides the entire sequence of coefficients and fits.

References

Zou and Hastie (2004) "Regularization and Variable Selection via the Elastic Net" In press, Journal of the Royal Statistical Society, Series B.

See Also

print, plot, enet

Examples

data(diabetes)
attach(diabetes)
object <- enet(x,y,lambda=0.1)
### make predictions at the values in x, at each of the
### steps produced in object
fits <- predict.enet(object, x, type="fit")
### extract the coefficient vector with L1 norm=2000
coef2000 <- predict(object, s=2000, type="coef", mode="norm")
### extract the coefficient vector with L1 norm fraction=0.45
coef.45 <- predict(object, s=0.45, type="coef", mode="fraction")
detach(diabetes)