On Wed, 2004-10-13 at 09:51, Prof Brian Ripley wrote:
> On Wed, 13 Oct 2004, Dan Bolser wrote:
> > I have a complex distance matrix, and I am thinking about how to cluster
> > it and how to visualize the quality of the resulting clusters.
>
> Using PCA and plotting the first two components is classical
> multi-dimensional scaling, as implemented by cmdscale(). Look up MDS
> somewhere (e.g. in MASS). It is exact if the distances are Euclidean in
> 2D. However, eurodist gives road distances on the surface of sphere.
>
> Classic examples for the illustration of MDS are departements of France
> based on proximity data and cities in the UK based on road distances.
>
These road distances seem to be very non-Euclidean indeed (even
non-metric). It seems to be 2282km from Athens to Milan if you go
directly, but if you go via Rome it is only 1403km:
> trip <- c("Athens", "Rome", "Milan")
> as.matrix(eurodist)[trip, trip]
Athens Rome Milan
Athens 0 817 2282
Rome 817 0 586
Milan 2282 586 0
> 817 + 586
[1] 1403
I thought that World is non-Euclidean, but not that obviously.
cheers, jari oksanen
--
Jari Oksanen <[EMAIL PROTECTED]>
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