Dear all,

Apologies in advance is this is not the right way to use the list; I'm a complete newbie to the concept (and partly to R). I just signed up searching for a solution to a geogr. data problem.

I've got a set of ~1,000 files on which I'd like to obtain the clusters with high density of points (using R code). I'm not really looking to plot & see the solution, as to calculate the points that matter (the geographical centers of the clusters), then save them.

These are the boundaries of my problem:


  *   Each file has 10K-50K points (long-lat, as in GPS).


  *   All files clearly have clusters (people stay longer times in certain spots). I'd like either the most relevant (no need to tell the function how many clusters are there in advance), or alternatively define a max. number and get at most those cluster centers.


  *   I've tried to use k-means but:  1) you need to know the no. of clusters in advance 2) It doesn't work for all shapes.


  *   I've tried hierarchical clustering (hclust) but it crashes for files with 30K points.


  *   I'm exploring using DBscan ('fpc' package), but I don't get how to see the centers of the clusters.

I know there are hundreds of packages out there, I'd just like some advice on which one to use considering this is (should be!) a relatively simple problem of getting a few coordinates out of every file.

Thanks in advance,   aud.

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