Hi Luca,
At the moment it's not returned from the R function, but you can do it
yourself by dividing the eigenvalues by the sum of squares of the
matrix entries and divide by n-1, as long as you use the same
standardisation as used for the PCA. For example,
f <- flashpca(X, ndim=10, tol=1e-6)
s <- sum(scale(X, center=f$center, scale=f$scale)^2) / (nrow(X) - 1)
pve <- f$values / s
cumsum(pve)
Gad
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