"predict"(object, newdata, pcs = nP(object), pre = TRUE, post = TRUE, ...)
"predict"(object, newdata, pcs = nP(object), pre = TRUE, post = TRUE, ...)
Arguments
object
pcaRes the pcaRes object of interest.
newdata
matrix new data with same number of columns
as the used to compute object.
pcs
numeric The number of PC's to consider
pre
pre-process newdata based on the pre-processing
chosen for the PCA model
post
unpre-process the final data (add the center back etc)
...
Not passed on anywhere, included for S3 consistency.
Value
A list with the following components:
scores
The
predicted scores
x
The predicted data
Details
This function extracts the predict values from a pcaRes object for
the PCA methods SVD, Nipals, PPCA and BPCA. Newdata is first
centered if the PCA model was and then scores ($T$) and data
($X$) is 'predicted' according to :
$That=XnewP$
$Xhat=ThatP'$. Missing values are
set to zero before matrix multiplication to achieve NIPALS like
treatment of missing values.