predict.spls {spls} | R Documentation |
Make predictions or extract coefficients from a fitted SPLS object.
## S3 method for class 'spls': predict( object, newx, type = c("fit","coefficient"), ... ) ## S3 method for class 'spls': coef( object, ... )
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 . |
Users can input either only selected variables or all variables for newx
.
Matrix of coefficient estimates if type="coefficient"
.
Matrix of predicted responses if type="fit"
.
Dongjun Chung, Hyonho Chun, and Sunduz Keles.
Chun, H. and Keles, S. (2009). "Sparse partial least squares for simultaneous dimension reduction and variable selection", To appear in Journal of the Royal Statistical Society - Series B (http://www.stat.wisc.edu/~keles/Papers/SPLS_Nov07.pdf).
plot.spls
and print.spls
.
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,]