[R] Multidimensional scaling and distance matrices
Federico Calboli
f.calboli at ucl.ac.uk
Thu Feb 26 16:05:02 CET 2004
On Thu, 2004-02-26 at 12:35, Christian Hennig wrote:
> Hi,
>
> usually the term MDS is used for methods which operate only on
> dissimilarity matrices. A similarity matrix s can be easily transformed
> into a dissimilarity matrix d by taking d <- max(s)-s, which could be
> considered as kind of a canonical standard to do this.
>
> It seems like the R-MDS methods give errors because your diagonals are
> larger and should be smaller than anything else for dissimilarities.
>
> I am not familiar with kinship matrices. You may try MDS on
> max(test)-test, but because the diagonals in your matrix are not equal I
> presume that there is another a bit more subtle standard routine to
> convert kinship matrices into dissimilarities, maybe something like
> (raw, not R) d(i,j)=1-s(i,j)^2/(s(i,i)s(j,j)).
>
I am happy with the function "dist" in {mva}, and I know there are other
functions in {cluster}, but it's besides the point. The question that is
nagging me is: is it justified to do a form of MDS on a matrix other
than a distance matrix? the reference I pointed out to do say to use a
distance matrix, but do not explicitely say "all else is wrong", so I
could call it a day.
> Did you consider the Statistica manual? It should tell you...
If I had it... in any case I hoped that the people that used Statistica
in the first place did read the manual before going forth in their
analysis. Now we are stuck in a situation where we do not know what
Statistica is actually doing, and I have to convince people that doing
things with R is going to be a better (= more sensible) option.
Regards,
Federico Calboli
--
=================================
Federico C. F. Calboli
Dipartimento di Biologia
Via Selmi 3
40126 Bologna
Italy
tel (+39) 051 209 4187
fax (+39) 051 251 208
f.calboli at ucl.ac.uk
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