I am using package ks() to build 3D representations of bird territories and
calculate territory volume from spatial data (simply x, y, and z
coordinates). What I want to do is determine at what sample size (#
locations collected) does the territory volume stop increasing. This should
give me an idea of the number of points needed for future seasons.
So I have a couple of birds each with 200 spatial locations (x,y,z). I want
to run the following code (see below), but have R calculate territory size
100 times with 10 random points (no replacement), 100 times with 20 random
points, 100 times with 30 random points, etc. I can figure out how to do
this manually (i.e. create 100 individual files with 10 random points, 20
random points, etc.) but I figure there must be a way to make my life
easier. Any help would be appreciated. Even pointing me in the correct
direction would be a big help. Thanks!
Nathan
#read data files (.csv's with 200 rows of x,y,z coordinates)
a<-read.csv("A_PW_ASY_M_LII_2011.csv")
#calls the plug-in bandwidth estimator
Ha <- Hpi(a)
#sets min/max grid size for each dimension
minX<-min(a$X)-25
minY<-min(a$Y)-25
minZ<-0
maxX<-max(a$X)+25
maxY<-max(a$Y)+25
maxZ<-max(a$Z)+5
#creates kernel utilization distribution
fhata <- kde(x=a, H=Ha, binned=FALSE, xmin=c(minX,minY,minZ),
xmax=c(maxX,maxY,maxZ))
#calculates territory volume at 95% isopleth
Vol95<-contourSizes(fhata, cont=95)
--
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