spls (version 2.2-3)

predict.spls: Make predictions or extract coefficients from a fitted SPLS model

Description

Make predictions or extract coefficients from a fitted SPLS object.

Usage

# S3 method for spls
predict( object, newx, type = c("fit","coefficient"), ... )
# S3 method for spls
coef( object, ... )

Arguments

object

A fitted SPLS object.

newx

If type="fit", then newx should be the predictor matrix of test dataset. If newx is omitted, then prediction of training dataset is returned. If type="coefficient", then newx can be omitted.

type

If type="fit", fitted values are returned. If type="coefficient", coefficient estimates of SPLS fits are returned.

...

Any arguments for predict.spls should work for coef.spls.

Value

Matrix of coefficient estimates if type="coefficient". Matrix of predicted responses if type="fit".

Details

Users can input either only selected variables or all variables for newx.

References

Chun H and Keles S (2010), "Sparse partial least squares for simultaneous dimension reduction and variable selection", Journal of the Royal Statistical Society - Series B, Vol. 72, pp. 3--25.

See Also

plot.spls and print.spls.

Examples

# NOT RUN {
data(yeast)
# SPLS with eta=0.7 & 8 latent components
f <- spls( yeast$x, yeast$y, K=8, eta=0.7 )
# Coefficient estimates of the SPLS fit
coef.f <- coef(f)
coef.f[1:5,]
# Prediction on the training dataset
pred.f <- predict( f, type="fit" )
pred.f[1:5,]
# }