## Re: [ai-geostats] Simulating an autocorrelated field

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• ... It is easy to simulate a Gaussian random field of given geometry with given spatial correlation function using the package RandomFields, in the free GNU
Message 1 of 3 , Jun 13, 2005
> Hi list,
>
> I need to generate a field f(x,y) with given variogram. More precisely, I
> have N points (x,y) and I want to assign f(x,y) such that the variable f
> has a spatial autocorrelation structure according to a given variogram
> model.
>
> My impression is that the way to do it is simulated annealing, as
> described in chapter 11 of the GSLIB manual. Is that correct ? Any other
> methods ? Is there any easy-to-use & free software for this purpose ? Any
> recommended literature ?

It is easy to simulate a Gaussian random field of given geometry with
given spatial correlation function using the package RandomFields, in the
free GNU statistical system R. For example, i could make N.sim such random
fields with a Gaussian variogram and save them all as text files with
these lines of code:
--------------
mcolasim9<-function(N.sim){
#Grid definition
x<-seq(1,180,1)
y<-seq(1,540,1)
#Variogram model
param<-c(6.63,2.24,1.82,4.36)
#Major loop
for(i in 1:N.sim){
mcola<-GaussRF(x=x,y=y,param=param,grid=TRUE,model="gauss")
file1.out<-paste("mcolasim9",i,"txt",sep=".")
write(t(mcola),file1.out,ncol=ncol(t(mcola)))
}
}
---------------
RandomFields will use simulated annealing if convenient but will use
another method if this other method is best for the case at hand, and will
select the method automatically. You can also force RandomFields to use a
given method if you want.
In R 2.1.0, from
citation("RandomFields")
i get
Martin Schlather, (). RandomFields: Simulation and Analysis of
Random Fields. R package version 1.2.16.
http://www.unibw-hamburg.de/WWEB/math/schlath/schlather.html
Cheers,
Ruben
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