[STATSGRASS] R/GRASS/Gaussian simulation issue

[Thomas Adams]

List:

I am attempting Gaussian simulation of modeled precipitation fields 
which are, of course, like all precipitation data decidedly non-normal. 
In order to do the simulations, the data must be transformed using a 
normal score transform. I can do this in R using:

z<-qnorm(ppoints(x)), where x is the precipitation field data.

This works and I can transform the data back to precipitation values. 
The problem I have is how do I do this maintaining the spatial patterns. 
That is, I read the data into R from GRASS:

precip<-readFLOAT6sp("data")

After I perform the Gaussian simulation of modeled *transformed* 
precipitation fields, I need to transform the data back to precipitation 
values maintaining geographic/spatial patterns. How do I do this?

Help is appreciated.

Regards,
Tom


-- 
Thomas E Adams
National Weather Service
Ohio River Forecast Center
1901 South State Route 134
Wilmington, OH 45177

EMAIL:	thomas.adams at noaa.gov

VOICE:	937-383-0528
FAX:	937-383-0033