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 the prediction of training dataset is returned.
If type="coefficient" , then newx can be omitted.
|
type |
If type="fit" , the fitted values are returned.
If type="coefficient" ,
the 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. (2007). "Sparse partial least squares for simultaneous dimension reduction and variable selection", (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,]