How to find singular matrix eigenvector?

0
votes

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?

1
reigenvectoreigenvalue
see eigen function (e.g. result$values[1] and result$vectors[,1]) - Marc in the box
@Marcinthebox, it's not working for singular matrix - user2080209
Ok, jumped the gun I guess. You may want to provide a small example. perhaps svd would find a solution where eigen does not. - Marc in the box
@Marcinthebox, can't find how to use swd for my problem - user2080209

1 Answers

1
votes

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.