[R] SVD on a matix

[Yasir Kaheil]

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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