Nick
The simplest way would be to do a aussian simulation and then do a rank
transfrom on the results, I think.
Isobel
http://www.kriging.com
--- On Tue, 17/11/09, Nick Hamm n...@hamm.org wrote:
From: Nick Hamm n...@hamm.org
Subject: AI-GEOSTATS: Unconditional simulation
To:
Dear all
I have a question about the random number seeding in R.
I want to simulate several random fields. Each RF should have zero
nugget, the same sill but a different range (e.g., 100x100, range: 1
- 30). Let's stick with the Gaussian case for now. I use the
following code
Hi Nick
One way is to use simulated annealing (see gslib) putting as objective
function your desired variogram and histogram.
(but I guess that by means of some data transformation you can do that
with a simple sequential gaussian simulation approach)
Bye
Sebas
At 10.06 17/11/2009, Nick Hamm
Nick Hamm :
Dear all
I have a question about the random number seeding in R.
Note that, for each simulation, I use the same random number seed.
This results in a series of images that look like they have the same
starting point (sorry, this is not very technical), but with
progressively
typos: it was phi, not sigma ... you'll get change at some phi
Anatoly Saveliev
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well Isobel explained how to go from Gaussian to uniform...
On Tue, Nov 17, 2009 at 1:59 PM, Anatoly Saveliev s...@ksu.ru wrote:
Pierre Goovaerts :
For once, I agree with Isobel.
sGs is the way to go...
sGs - Gaussian by definition; he wants uniform :-)
Anatoly Saveliev
Pierre
On
