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 Chizé-CNRS UPR1934
79360 Beauvoir sur Niort
Phone +33 (0)5 49 09 96 13
Fax +33 (0)5 49 09 65 26
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