Hi: Not sure if totally relevant because I didn't read it but it might help
or atleast
be of interest.

http://journal.r-project.org/archive/2010-1/RJournal_2010-1_Wilhelm+Manjunath.pdf


On Mon, Nov 12, 2012 at 12:15 PM, Ben Bolker <bbolker@gmail.com> wrote:

> Zhenglei Gao <zhenglei.gao <at> bayer.com> writes:
>
> >  I have asked the same question on stackoverflow but did not get a
> > satisfying answer.
>
> > I am trying to simulate a lognormal spatial random field but I need
> > the simulated value in a certain range. So I need some easy to use
> > functions to generate a truncated Gaussian field to start with. To
> > be specific, I need a function like GaussRF from the RandomFields
> > package or grf from the geoR package to generate a random field, but
> > I need the generated field to have a truncated marginal
> > distributions and a correlation structure with a prescribed
> > range. Is there an R package or functions which can do this? If
> > there is no availabe read-to-use functions or packages,is it
> > possible that I write my own very easily?
>
>   As I suggested on Stack Overflow, I don't think this is a simple
> question: you can pick values according to a normal distribution and
> then squash them into a truncated normal distribution: something like
>
> olddata <- GaussRF(...)
> library(truncnorm)
> newdata <- qtruncnorm(pnorm(olddata))
>
>   However, this may very well modify the range; I don't know.
> If I were you, I would try it and see if you can live with the
> results.  If not, ask on http://stats.stackexchange.com
>
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