Hello, I have a data set with 15 variables (first one is the response) and 1200 observations. Now I use pls package to do the plsr as below.
trainSet = as.data.frame(scale(trainSet, center = T, scale = T)) trainSet.plsr = mvr(formula, ncomp = 14, data = trainSet, method = "kernelpls", model = TRUE, x = TRUE, y = TRUE) from the model, I wish to know the values of Xvar (the amount of X-variance explained by each number of components) and Xtotvar (total variance in X). Because the trainSet has been scaled before training, I think Xtotvar should be equal to 14, but unexpectedly Xtotvar = 16562, and the values of Xvar are also very big and sum of Xvar = 16562. Why does this type of result occur? for the reason of kernel algorithm? Thank you, Shengzhe ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html