Re: [R] Difference between prcomp and cmdscale

From: michael watson (IAH-C) <>
Date: Thu, 14 Jun 2007 13:52:40 +0100

Hi Mark

I think Brian Ripley answered this most effectively and succinctly. I did actually do quite a bit of googling and searching of the R help before posting, and whilst there is quite a lot on each topic individually, I failed to find articles that compare and contrast PCA and MDS. If you know of any, of course I would be happy to read them.

Many thanks

-----Original Message-----
[] On Behalf Of Mark Difford Sent: 14 June 2007 12:49
Subject: Re: [R] Difference between prcomp and cmdscale


Why should that confuse you? Have you tried reading some of the literature
on these methods? There's plenty about them on the Net (Wiki's often a goodish place to start)---and even in R, if you're prepared to look ;).


michael watson (IAH-C) wrote:
> I'm looking for someone to explain the difference between these
> procedures. The function prcomp() does principal components anaylsis,
> and the function cmdscale() does classical multi-dimensional scaling
> (also called principal coordinates analysis).
> My confusion stems from the fact that they give very similar results:
> my.d <- matrix(rnorm(50), ncol=5)
> rownames(my.d) <- paste("c", 1:10, sep="")
> # prcomp
> prc <- prcomp(my.d)
> # cmdscale
> mds <- cmdscale(dist(my.d))
> cor(prc$x[,1], mds[,1]) # produces 1 or -1
> cor(prc$x[,2], mds[,2]) # produces 1 or -1
> Presumably, under the defaults for these commands in R, they carry out
> the same (or very similar) procedures?
> Thanks
> Mick
> The information contained in this message may be\ confiden...{{dropped}} mailing list PLEASE do read the posting guide and provide commented, minimal, self-contained, reproducible code. Received on Thu 14 Jun 2007 - 13:00:08 GMT

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