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...@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]] >> >> ______________________________________________ >> r-h...@r-project.org mailing >> listhttps://stat.ethz.ch/mailman/listinfo/r-help >> PLEASE do read the posting >> guidehttp://www.R-project.org/posting-guide.html >> and provide commented, minimal, self-contained, reproducible code. > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > > -- View this message in context: http://www.nabble.com/PCA-functions-tp22006964p22034611.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
