Hey Nathan, You might like the DBSCAN algorithm.
http://en.wikipedia.org/wiki/DBSCAN There's an implementation in the 'fpc' package. http://cran.r-project.org/web/packages/fpc/index.html -Mose On Sun, Jun 14, 2009 at 7:36 PM, Dylan Beaudette<dylan.beaude...@gmail.com> wrote: > On Sun, Jun 14, 2009 at 7:26 PM, Nathan S. > Watson-Haigh<nathan.watson-ha...@csiro.au> wrote: >> -----BEGIN PGP SIGNED MESSAGE----- >> Hash: SHA1 >> >> Dylan Beaudette wrote: >>> On Sun, Jun 14, 2009 at 4:39 PM, Nathan S. >>> Watson-Haigh<nathan.watson-ha...@csiro.au> wrote: >>>> -----BEGIN PGP SIGNED MESSAGE----- >>>> Hash: SHA1 >>>> >>>> Is there a library which is capable of identifying distinct clusters of >>>> size n >>>> from a series of XY coordinates? >>>> >>>> Failing this, I'd like to be able to to something like: >>>> Using a sliding window of size n along the x-axis I'd like to determine the >>>> distance between the center of the points in the window and the closest >>>> point >>>> outside the window. I could then use a distance cutoff to help define my >>>> clusters of size n. However, how can I calculate this distance? >>>> >>>> Cheers, >>>> Nathan >>>> >>> >>> Here is a start, using PAM clustering: >>> >>> http://casoilresource.lawr.ucdavis.edu/drupal/node/340 >>> >>> cheers, >>> Dylan >> > > Hi, > >> >> Thanks, that looks interesting. However I need a clustering algorithm which >> has >> the following properties: >> >> 1) The ability to define clusters of size n >> 2) No need to specify a priory how many clusters there will be >> 3) The ability to omit data from any cluster. I don't think this package can >> do >> this. > > Time to do some reading on the various clustering algorithms, their > assumptions, and their overall behaviour. Although I am not an expert, > many of the constraints you are trying to impose on the clustering > will require some kind of programming / decision on your end. It may > help to re-formulate the problem into some kind of raster-operation, > in which case GRASS GIS might be of interest to you. > >> I suspect for something like this I'll have to define, a priory, how tight >> points within a cluster should be using some measure. >> > > Hmm... In this case you may need to use a model-based / or > density-based approach. See mclust and spatstat packages. (???) > > Cheers, > > Dylan > >> Any thoughts? >> Nathan >> >> - -- >> - -------------------------------------------------------- >> Dr. Nathan S. Watson-Haigh >> OCE Post Doctoral Fellow >> CSIRO Livestock Industries >> Queensland Bioscience Precinct >> St Lucia, QLD 4067 >> Australia >> >> Tel: +61 (0)7 3214 2922 >> Fax: +61 (0)7 3214 2900 >> Web: http://www.csiro.au/people/Nathan.Watson-Haigh.html >> - -------------------------------------------------------- >> >> -----BEGIN PGP SIGNATURE----- >> Version: GnuPG v1.4.9 (MingW32) >> Comment: Using GnuPG with Mozilla - http://enigmail.mozdev.org >> >> iEYEARECAAYFAko1sWMACgkQ9gTv6QYzVL7grwCZAQh72v33vPNJJgEFJEhfyNc3 >> 718AnA3k7wvvLEZ4NS1enW3Xp5WhO+qJ >> =1gyG >> -----END PGP SIGNATURE----- >> > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
