Dear Miha (cc: Paulo Ribeiro [the developer of geoR, who is not subscribed to R-help])
Some reproducible code would help here.
Unfortunately I do not have an internet connect on my computer, that is why I did every thing very descriptive. Anyway I will try:
str(df)
[#approx 2500]
$ x ...
$ y ...
$ z ...
library(geoR)
g<-as.geodata(df)
expvar<-variog(g, uvec=seq(0,1000,25), option="bin")
matern<-variofit(expvar, ini=c(1600,300), cov.model="matern", fix.nug=T, nug=25, kappa=1.5, max.dist=800, weights="npairs")
library(GRASS)
G<-gmeta()
grid<-expand.matrix(G$xseq,G$yseq)
length(G$xseq)
900 #approx
length(G$yseq)
650 #approx
krige.matern<-krige.conv(g, loc=grid, krige=krige.control(obj.m=matern, type="OK"))
#5 min processing can not allocate vector of 1500000000 #approx
Thanks, Miha Staut
Guessing :
* geoR does not implement kriging with local neighbourhoods, but instead conditions on all data. Therefore having 2500 data points would imply having a covariance matrix of size 2500*2500 approx 6million . Not sure if this is too much, but I do not think so.
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