[R] PCA functions
andrew
andrewjohnroyal at gmail.com
Mon Feb 16 11:55:36 CET 2009
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 Bjørn-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
>
> >> [[alternative HTML version deleted]]
>
> >> ______________________________________________
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>
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