Also new values can be easy calculated from prcomp object:
Data - scale(iris[,1:4],center=TRUE,scale=TRUE)
iris.pc - prcomp(Data)
# Explained variation
(iris.pc$sdev^2/sum(iris.pc$sdev^2))*100
# Loadings
iric.pc$rotation
#Scores
iris.pc$x
#Fitted Values for each PC
# Xfit = T*P^t
PCfit -
See ?rconst in package ade4. You will need to fit the PCA with
dudi.pca (same package).
Best,
Renaud
2006/11/9, Poizot Emmanuel [EMAIL PROTECTED]:
Dear all,
I did performed a PCA analysis (using prcomp function) on a data matrix.
Then I would like to reconstruction part of the original data
