Re: distribution transformations and Gstat

["Edzer J. Pebesma" <edzer@pangea.Stanford.EDU>]

Ashton Shortridge wrote:
> performing gaussian simulation using Gstat is remarkably straightforward
> - it's a great resource for spatial modeling! However often the
> underlying datasets are not normally distributed. A workaround is to
> transform the data, do the simulation, and backtransform, as can be done
> in GSLIB. I'm writing to see if anyone has developed this approach for
> Gstat, and if so, what additional data processing tools have been
> employed.

There is no such thing automatic in gstat, and the only transformations
provided are log and indicator transform. However, results are not
transformed back, so it's only pre-processing that's been done by
gstat.

I don't know how this is done by GSLIB -- do they use a parametric
transform, or do they use rank order transforms? In the latter case,
how do they transform back values outside the observed range? (I have
the GSLIB 2 book here, but you may know it straight away?)

Is this something we could automate easily, or is would that take
too much responsibility away from the user? Any opinions?
--
Edzer