Good morning (and sorry for the cross posting on the R sig ecology),
I'm still working on the spatial distribution of an aggregated bird species. I would like to test different between birds distances to create clusters and thus identify groups of birds (leks). It would be "visually" quite easy to do it but I would like to repeat this clustering objectively for many years in order to characterize some biological processes. So I would like for example to group all the birds who share neighbours in less than 1000 meters in the same cluster. Thus, 3 birds lying on a straight line 700 meters from each other would belong to the same cluster (hope this is clear).
I can get groups of points whose distances are below a certain threshold with dnearneigh() from package "spdep" but this would still require to write an iterative function to group points.
Is there an existing function that can do the whole trick? I know many packages are available for clustering with R but I haven't found one that I can parametrize in a such way yet.
Any link will be appreciated.
Thanks
Alex
P.S.: to get this visually
x<-c(0,700,1400, 3000)
y<-c(0,0,0,0)
plot(y~x, col=c("red","red", "red", "black"), pch=c(16,16,16,16)) # red points belong to the same cluster while the black doesn't
Alexandre Villers PhD Candidate AgriPop Centre d'Etudes Biologiques de Chiz?-CNRS UPR1934 79360 Beauvoir sur Niort Phone +33 (0)5 49 09 96 13 Fax +33 (0)5 49 09 65 26 __________ Information from ESET Mail Security, version of virus signature database 4674 (20091209) __________ The message was checked by ESET Mail Security. http://www.eset.com