How to generate a random field with truncated marginal distributions?

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 at gmail.com
<mailto:bbolker at gmail.com>> wrote:

    Zhenglei Gao <zhenglei.gao <at> bayer.com <http://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