How to find singular matrix eigenvector?

Question

I have a 800x800 singular (covariance) matrix and I want to find it's largest eigenvalue and eigenvector corresponding to this eigenvalue. Does anybody know wheter it is possible to do it with R?

Answer 1

Here is an example of using svd for the decomposition of a covariance matrix:

a <- matrix(runif(16),4)
C <- cov(a)
res <- svd(C)
res
res$d[1] # largest singular value
res$u[,1] # largest vector ; u and v are the same

Hope that helps.