On 12/05/2011 13:12, Matevž Pavlič wrote:
Hi all,
I have a point data set (SHP) with coordinates and a attribute (i.e. type of
point).
These points are scattered around a fairly big area. What i would like to do is
to find a sub-area where density of points sombined with the diversity of type
is the biggest.
Does anyone have any idea iff this is somehowe possible to do in R? Any idea
would be greatly aprpeciated,
To your first question:
library(fortunes)
fortune("Yoda")
;-)
More seriously, you could transform your shp data in a ppp object with
spatstat. See the vignette in spatstat. Then you can use some functions
there, for example (with the data set lansing):
library(spatstat)
data(lansing)
plot(lansing)
# get an estimate of point density
lansing.den <- density.ppp(lansing)
plot(lansing.den)
# get an estimate of point diversity (here, for the shake of brevity, at
the points themselves)
lansing.tab<- marktable(lansing,R=0.05)
diversity <- apply(lansing.tab,1,function(x) sum(x>0))
lansing.div <- setmarks(lansing,diversity)
lansing.div.s <-smooth.ppp(lansing.div)
plot(lansing.div.s)
# select areas with arbitrary high values of density and diversity
plot(eval.im(lansing.div.s >4.5 & (lansing.den/max(lansing.den))>0.9))
HTH. Cheers,
Marcelino
--
_________________________________
Marcelino de la Cruz Rot
Departamento de Biologia Vegetal
E.U.T.I. Agricola
Universidad Politecnica de Madrid
28040 Madrid
Tel: 34913365654
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