spls (version 2.3-2)

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, ... )

Value

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

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.

Author

Dongjun Chung, Hyonho Chun, and Sunduz Keles.

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

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,]