Hi,
If you are only interested in row means, you can work the distance
matrix at the c level.
You might like to adapt this post:
http://tolstoy.newcastle.edu.au/R/e6/devel/09/04/1378.html
Romain
On 06/26/2009 09:40 PM, leif olson wrote:
Hello, Im working on a 50933 point count bird abundance dataset. I've
succeeded in calculating a distance matrix for this entire set, but I don't
have sufficient memory to convert this to a matrix, as below...
abun.dist<- dist(abun.mat[1:50993,1:235)
test<- rowMeans(as.matrix(abun.dist))
Error in matrix(0, size, size) : too many elements specified
ive been able to run a hclust() clustering procedure, due to the fact that
hclust() makes a call to fortran code, but id like to be able to generate a
calinski index for each of the clusters to assess the validity.
Unfortunately, all the validation routines I have found are all native R
code, and usually call as.matrix, resulting in the same error i receive
above.
What I'd like to figure out is how to just go through, one point at a time,
and calculate the values i need. But I've been unable to come up with code
to call the correct positions in the dist vector, can anyone suggest some
code that might do this? Thanks...
...leif
--
Romain Francois
Independent R Consultant
+33(0) 6 28 91 30 30
http://romainfrancois.blog.free.fr
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