Mateus,
I see what you mean.
I can't figure it out.
I found a message from a few years ago that mentions the same problem.
http://tolstoy.newcastle.edu.au/R/e8/help/09/12/8165.html
This may be a bug.
Since hclust() is in the stats package, I am ccing the maintainer,
r-c...@r-project.org, on this e-mail.
Jean
> find("hclust")
[1] "package:stats"
> maintainer("stats")
[1] "R Core Team <r-c...@r-project.org>"
Mateus Teixeira <mateus.teixe...@gmail.com> wrote on 07/04/2012 07:39:39
AM:
> Dear R users,
>
> I have noted a difference in the merge distances given by hclust using
> centroid method.
>
> For the following data:
>
> x<-c(1009.9,1012.5,1011.1,1011.8,1009.3,1010.6)
>
> and using Euclidean distance, hclust using centroid method gives the
> following results:
>
> > x.dist<-dist(x)
> > x.aah<-hclust(x.dist,method="centroid")
> > x.aah$merge
> [,1] [,2]
> [1,] -3 -6
> [2,] -1 -5
> [3,] -2 -4
> [4,] 1 2
> [5,] 3 4
> > x.aah$height
> [1] 0.50000 0.60000 0.70000 0.97500 1.36875
>
> A calculation by hand results same merges, but at different distances
for
> latter stages:
>
> heights:
> 0.5 => merging 3 and 6 => G1
> 0.6 => merging 1 and 5 => G2
> 0.7 => merging 2 and 4 => G3
> *1.25 => merging G1 and G2 => G4
> 1.92 => merging G3 and G4*
>
> It seems that hclust is not correctly computing the group centroids. Is
it
> correct?
>
> Best regards,
>
> Mateus
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