Re: AI-GEOSTATS: Back transforms and simulations
Many thanks to Isobel Clark and Pierre Goovaerts for sending replies to
my email about simulation and back transforms. Both pointed out that in
the case of simulation the back transform is straightforward. Pierre
also noted that GSLIB allows normal scores transforms and back
transforms, which are more flexible than log transforms.
Both replies are copied below.
Since your simulated values should have the same distribution as the
original data, you simply need to anti-log.
I prefer to use 'natural' logarithms for transformation and then do
e-to-the-x, but using logs to the base 10 and then 10-to-the-x should
as well. The answer is rather more complicated if you krige with logs to
the base 10.
The back transform of simulated values is very easy to perform. Just
take the exponential of the simulated values since you are not trying to
estimate the mean of the local probability distribution in the original
space, but only a quantile of this distribution. Note that if you
perform SGS using Gslib, there is a built-in normal score transform and
back-transform in the program, which is more flexible than the lognormal
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