Pierre,
Thank you very much for your response. I actually had not attempted
transforming the data yet — this was one of the questions I had in my
mind, namely, whether or not the transformation would do this. Regarding
the transformation, would a z-score or, perhaps, a Box-Cox, or some
other
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.
R
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, u
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 cos
Hallo!
I'm a Ph.D. students who works with Indoor Radon Data, and it's the
first time I join this list. I've a question for you: after
post-processing several Sequential Gaussian Simulation to obtain a
probability map of exceeding a given threshold, can someone suggests
me a "clever" way to "vali
