PCA functions
sqrt(svd(x)$d) maybe 2 more operations than princomp(covmat=x), but it is hardly a chore.
On Feb 16, 9:15?pm, Mark Difford <mark_diff... at yahoo.co.uk> wrote:
Hi Glen, Andrew,
The PCA is just a singular value decomposition on a sample covariance/...
I believe that Bj?rn-Helge Mevik's point was that __if you read the documentation__ you will see the argument "covmat" to princomp(). This, really, is much more straightforward and practical than Andrew's suggestion. Regards, Mark. andrew-246 wrote:
The PCA is just a singular value decomposition on a sample covariance/ correlation matrix. ?Do a search for ?svd and get the eigenvalues and vectors from that function.
On Feb 14, 10:30?am, "glenn" <g1enn.robe... at btinternet.com> wrote:
Hi All, would appreciate an answer on this if you have a moment;
Is there a function (before I try and write it !) that allows the input of a covariance or correlation matrix to calculate PCA, rather than the actual data as in princomp()
Regards
Glenn
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