Thank you, Jean.
Mateus
2012/7/6 Jean V Adams
> 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-core@r-project.org, on this e-mail.
>
> Jean
>
> > find("hclust")
> [1] "package:stats"
> > maintainer("stats")
> [1] "R Core Team "
>
>
>
> Mateus Teixeira 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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