Paulo,
 Thank you for your quick reply. You've been very helpful. This work is part 
of my master thesis, so I want to make sure it works ok. Will The
krige.convcommand be fine to test sampling design from a conditionally
simulated data
set? What i mean is will the new new data set produced follow the same 
variogram model, or one very close to the original?
 Thank you for any help
 -Matthew Sokol 

 On 5/23/05, Paulo Justiniano Ribeiro Jr <paulojus@est.ufpr.br> wrote: 
> 
> Hi Matthew
> 
> It is important to distinghish between "conditional" (on the data)
> and "unconditional" simulations
> 
> krige.conv() will do the former whereas
> grf() will perform the latter
> 
> In other words, conditional simulation will follows the observed data
> closely.
> Unconditional simulation will just take a different sample of the same
> model and it is natural to have a quite diferent simulation with ups and
> downs in different locations -
> your call to grf() will produce a simulation which is stocastically
> independent of the s100 data - so a quite different aspect.
> 
> 
> 
> On Mon, 23 May 2005, Matthew Sokol wrote:
> 
> > Hello,
> >
> > My name is Matthew Sokol and I am using the package geoR and I am having 
> a
> > little trouble using the "grf" function.
> >
> > What I am trying to do is to simulate data that follows the same 
> variogram
> > model as a certain data set.
> >
> > So I start with the built in data set s100.
> >
> > It says that it has a Sill equal to one and a range equal to .3 based on
> > the following commands:
> >
> > plot(variog(s100,max.dist=1))
> >
> > lines.variomodel(cov.model = "exp", cov.pars = c(1, 0.3),nug = 0,
> max.dist=1)
> >
> > loci <- expand.grid(seq(0,1,l=21), seq(0,1,l=21))
> >
> > kc <- krige.conv(s100, loc=loci,krige=krige.control(cov.pars=c(1, .3)))
> >
> > image(kc)
> >
> > Now what I want to do is to simulate data on the same grid that follows 
> the
> > same variogram model. So I run the following commands:
> >
> > sims100 <- grf(100, ylims=c(0,0), cov.pars=c(1,.3), nugget = 0, 
> cov.model=
> > "exp")
> >
> > simkc <- krige.conv(sims100, loc=loci,krige=krige.control(cov.pars=c(1,
> > .3)))
> >
> > image(simkc)
> >
> > But when you compare the two images of 'kc' and 'simkc' they are nothing
> > alike.
> >
> > What I am ultimately trying to do is create a new data set within my
> > original location that accurately reflects the original data. Then I 
> would
> > like to resample the data to see how different sampling locations affect 
> OK
> > and OK stand deviation.
> >
> > Would re-sampling from the data set 'kc' be ok here since the
> > krige.convcommand creates a new data set based off the original model
> > at new locations
> > ( i.e. the location "loci").
> >
> > I am not sure if I am running the commands wrong or if I am using the
> > functions totally wrong. I am a novice at best when it comes to using R, 
> and
> > I hope anyone can point me in the right direction.
> >
> > Thanks in advance for any help.
> >
> > -Matthew Sokol
> >
> > [[alternative HTML version deleted]]
> >
> > _______________________________________________
> > R-sig-Geo mailing list
> > R-sig-Geo@stat.math.ethz.ch
> > https://stat.ethz.ch/mailman/listinfo/r-sig-geo
> >
> >
> 
> Paulo Justiniano Ribeiro Jr
> LEG (Laboratório de Estatística e Geoinformação)
> Departamento de Estatística
> Universidade Federal do Paraná
> Caixa Postal 19.081
> CEP 81.531-990
> Curitiba, PR - Brasil
> Tel: (+55) 41 3361 3573
> Fax: (+55) 41 3361 3141
> e-mail: paulojus@est.ufpr.br
> http://www.est.ufpr.br/~paulojus
>

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