Hi Stefano,
First, I am not sure that stochastic simulation is necessary in your case
since you seem to be only interested in what I would call a measure
of local (or location-specific) uncertainty. MultiGaussian kriging would in
theory
give you exactly the same results at less computational
List:
I am interested in doing some geostatistical simulations using GSTAT and
have some theoretical questions.
I am attempting to model hourly rainfall accumulations over a large
region, so there will almost always be zero rainfall somewhere. I can
generate random fields of precipitation,
Hi Thomas,
I am assuming that you transform your data before conducting
your (sequential?) Gaussian simulation. In this case, the backtransform
would yield only positive values, assuming of course that like S-GeMS Gstat
asks the user to specify the minimum and maximum of the target histogram.
