Description Usage Arguments Value Author(s) Examples
Why? plclust is great for plotting heirarchical clusters; rect.hclust is great for selecting clusters at a given distance threshold; what is lacking is knowing which clusters are which. This is espescially useful if you then do some downstream analysis on each cluster, if you end up referring to your clusters numerically.
1 2 |
tree |
see rect.hclust. NB this must be identical to those used in your call to rect.hclust |
k |
see rect.hclust. NB this must be identical to those used in your call to rect.hclust |
which |
see rect.hclust. NB this must be identical to those used in your call to rect.hclust |
x |
see rect.hclust. NB this must be identical to those used in your call to rect.hclust |
h |
see rect.hclust. NB this must be identical to those used in your call to rect.hclust |
border |
see rect.hclust. NB this must be identical to those used in your call to rect.hclust |
cluster |
see rect.hclust. NB this must be identical to those used in your call to rect.hclust |
annotates a plot with indices
Mark Cowley, 2009-10-30
1 2 3 4 5 | m <- matrix(rnorm(200), nrow=20)
hc <- hclust(dist(m))
plot(hc)
rect.hclust(hc, k=5)
rect.hclust.labels(hc, k=5)
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