predict.gamsel: Gamsel Prediction Routine

In gamsel: Fit Regularization Path for Generalized Additive Models

Description

Make predictions from a gamsel object.

Usage

## S3 method for class 'gamsel'
predict(
  object,
  newdata,
  index = NULL,
  type = c("link", "response", "terms", "nonzero"),
  ...
)

Arguments

object	Fitted gamsel object.
newdata	nobs_new x p matrix of new data values at which to predict.
index	Index of model in the sequence for which plotting is desired. Note, this is NOT a lambda value.
type	Type of prediction desired. Type link gives the linear predictors for "binomial", and fitted values for "gaussian". Type response gives fitted probabilities for "binomial" and fitted values for "gaussian". Type "terms" returns a matrix of fitted functions, with as many columns as there are variables. Type nonzero returns a list of the indices of nonzero coefficients at the given lambda index.
...	Not used

Value

Either a vector aor a matrix is returned, depending on type.

Author(s)

Alexandra Chouldechova and Trevor Hastie
Maintainer: Trevor Hastie [e-mail]

References

Chouldechova, A. and Hastie, T. (2015) Generalized Additive Model Selection

See Also

gamsel, cv.gamsel, summary.gamsel, basis.gen

Examples

##data=gamsel:::gendata(n=500,p=12,k.lin=3,k.nonlin=3,deg=8,sigma=0.5)
data = readRDS(system.file("extdata/gamsel_example.RDS", package = "gamsel"))
attach(data)
bases=pseudo.bases(X,degree=10,df=6)
# Gaussian gam
gamsel.out=gamsel(X,y,bases=bases)
preds=predict(gamsel.out,X,index=20,type="terms")

gamsel documentation built on Feb. 4, 2022, 5:09 p.m.