Thanks to Prof. Ripley for responding to my previous question.
I would like to clarify my question using sample code. I will use some sample code taken from ?prcomp
Again, I would like to compare the % variance explained by each PC before and after rotation.
< code follows >
data(USArrests) pca = prcomp(USArrests, scale = TRUE)
# proportion variance explained by each PC prop = pca$sdev^2/sum(pca$sdev^2)
# cumulative proportion variance explained by each PC cumProp = cumsum(prop)
# following print statements also can be obtained # from print(summary(pca)) #print(prop) #print(cumProp)
print(summary(pca))
# Rotate the PCA loadings through PCs 1 and 2 using VARIMAX rotation
rot = varimax(pca$rotation[,1:2], normalize = TRUE, eps = 1e-5)
< end code >
How can I calculate the new % variance explained by each PC after rotation ??????
Many thanks once more,
-- Maurice J. McHugh, Ph.D.
Assistant Professor Department of Geography and Anthropology 227 Howe Russell Geoscience Complex Louisiana State University Phone: (225)578-0476 Baton Rouge, LA Fax: (225)578-4420 USA
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