I am to do as follows: I have a set of Vektors v1-vn For these, I need the covariance matrix (which I get while doing a pca). I also need the eigenvalues and eigenvectors of the covariance matrix. The eigenvalues I sort in descending order and then I sort the eigenvectors according to their corresponding eigenvalues. After that I multiply v1 with the first of the eigenvectors, v2 with the second and so on. I return the skalar which I get in this way.
Is there any simple way in R to see which eigenvalue corresponds to which eigenvector?
Use the result of prcomp
directly. It sorts the eigenvalues from biggest to smallest.
p <- prcomp(USArrests, scale=T)
For appropriate values of i
, the eigenvalue is p$sdev[i]^2
, with eigenvector p$rotation[,i]