Hi Ayesha,
hclust is a way to go (much better then trying to invent the wheel here).
Please add what you used to create:
distA
And create a sample data set to show us what you did, using
dput
Best,
Tal
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On Fri, May 28, 2010 at 2:41 AM, Ayesha Khan <ayesha.diamond...@gmail.com>wrote:
> i have a matrix with the following dimensions
> 136 3
>
> and it looks something like
>
> [,1] [,2] [,3]
> [1,] 402 675 1.802758
> [2,] 402 696 1.938902
> [3,] 402 699 1.994253
> [4,] 402 945 1.898619
> [5,] 424 470 1.812857
> [6,] 424 905 1.816345
> [7,] 470 905 1.871252
> [8,] 504 780 1.958191
> [9,] 504 848 1.997111...............
>
> ................................................................................
> so you get the idea. I want to group similar items in one group/cluster
> following the "friends of friends" approach. I tried doing
>
> distclust <- hclust(distA,method="single")
> However, I got the following error.
>
> Error in if (n < 2) stop("must have n >= 2 objects to cluster") : argument
> is of length zero
> which probably means there's something wrong with my input here. Is there
> another way of doing this kind of clustering without getting into all the
> looping and ifelse etc. Basically, if 402 is close to 675,696,and699 and
> thus fall in cluster A then all items close to 675,696,and 699 should also
> fall into the same cluster A following a friends of friedns strategy.
> Any help would be highly appreciated.
>
> --
> Ayesha Khan
>
> MS Bioengineering
> Dept. of Bioengineering
> Rice University, TX
>
> [[alternative HTML version deleted]]
>
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>
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