On Thu, Dec 15, 2011 at 10:47 AM, Lorenzo Isella
wrote:
> Thanks a lot!
> Precisely what I had in mind.
> One last question (an extension of the previous one): can this be extended
> to points in 3D? Once again, given the distance matrix, can I reconstruct a
> set of coordinates (among many possib
Thanks a lot!
Precisely what I had in mind.
One last question (an extension of the previous one): can this be
extended to points in 3D? Once again, given the distance matrix, can I
reconstruct a set of coordinates (among many possible) for the points in
three-dimensional space?
Cheers
Lorenzo
On Thu, Dec 15, 2011 at 10:08 AM, Lorenzo Isella
wrote:
> Dear All,
> I am struggling with the following problem: I am given a NxN symmetric
> matrix P ( P[i,i]=0, i=1...N and P[i,j]>0 for i!=j) which stands for the
> relative distances of N points.
> I would like use it to get the coordinates of
That's exactly what ordination is for (not clustering).
I'd try principal coordinates analysis, or non-metric multidimensional
scaling, depending on whether the dissimilarity you'v been given is
metric or nonmetric.
There are implementations of both in the ecodist package, and in
various other pa
Dear All,
I am struggling with the following problem: I am given a NxN symmetric
matrix P ( P[i,i]=0, i=1...N and P[i,j]>0 for i!=j) which stands for the
relative distances of N points.
I would like use it to get the coordinates of the N points in a 2D
plane. Of course, the solution is not uniq
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