Re: [R] SVD on a matix

From: Yasir Kaheil <>
Date: Sun, 25 May 2008 00:09:20 -0700 (PDT)

the variance is the eigen values of the correlation matrix of yoru matrix

X.cor <- cor(X)
X.e <- eigen(X.cor)
X.e$values# Eigenvalues of cor(X) = variances you're asking about

kayj wrote:
> Hi All,
> I performed an svd on a matrix X and saved the first three column of the
> left singular matrix U. ( I assume that they correspond to the projection
> of the matrix on the first three eigen vectors that corresponds to the
> first three largest eigenvalues). I would like to know how much variance
> is explained by the first eigenvectors? how can I find that.
> Thanks for your help

Yasir H. Kaheil
Catchment Research Facility
The University of Western Ontario
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