[R] question about stdize() in PLS package

[jz7 at duke.edu]

Dear all,

I am using the PLS package for PLSR analysis. And I have a basic question
about the standardize procedure, which I feel the PLS manual does not
explain clearly. I am hoping that I could get some help from the list.

>From the example in the "Standardization of Data Matrices" section, I can
standardize X matrix and make prediction by using:

mod=plsr(y~stdize(X),ncomp=6,data=NIR[NIR$train,])
pred=predict(mod,newdata=NIR[!NIR$train,])

In the manual, it is commented that the prediction is "automatically
standardized". So I guess I won't need to standardize X matrix of the test
set for the prediction.

However, what if I do not want a standardize model from the beginning?
Then my code would be like:

mod=plsr(y~X,ncomp=6,data=NIR[NIR$train,])

But the R code for the prediction should still be the same (please
correct me if any code is wrong):

pred=predict(mod,newdata=NIR[!NIR$train,])

Would this time the X matrix of the newdata be automatical standardized or
not?

I am so confused about the "automatically standardization". Please share
some experience. Really appreciate your kind help!

Sincerely,
Jeny