[R-sig-Geo] Box-cox transformation and Conditional Sequential Gaussian Simulation!

[Zia Ahmed]

Thank you so much! I have used Box-cox transformation. I need to sure 
before submitting my paper for publication.
I used following codes for CSGS  of ground water arsenic concentration.

Zia

data(tala)

was.bc<-box.cox(tala$was, 0.47) 
tala.bc = cbind(tala, was.bc)

coordinates(tala.bc) <- ~ x + y  
coordinates(tala.grid) <-~ x + y 

v.ok.was<-variogram(was.bc~1,data=tala.bc)
plot(v.ok.was, pl=F, pch=20, cex=1, col="Black")
m.ok.was<-vgm(.06,"Exp",4000,0.02)
(m.ok.f.was<-fit.variogram(v.ok.was, m.ok.was))

# Simulation
#--------------
set.seed(130)
sim.was<-krige(was.bc~1,tala.bc,tala.grid,model=m.ok.f.was, nmax=50, 
nsim = 1000)

# Back-transformation
#-----------------
for(i in 1:length(sim.was at data)){sim.was at data[[i]] <- 
(((sim.was[[i]]*0.47+1)^k.was))}
sim.data.was<-as.data.frame(sim.was)
summary(sim.data.was)




Edzer Pebesma wrote:
> Yes, you can. It is less flexible than the normal score transform -- try
> for instance transforming a bimodal distribution -- but has the
> advantage that the back-transform is straightforward. How do you for
> example use the inverse normal score transformation simulated values
> outside the range of the data?
>
> Zia Ahmed wrote:
>   
>> I have a basic question related  to the data transformation CSG
>> simulation. Can  I use Box-cox transformation of the data instead of
>> normal score transformation before performing  CSG simulation?
>> Suggestion will be appreciated.
>> Thanks
>> ZIa
>>
>> _______________________________________________
>> R-sig-Geo mailing list
>> R-sig-Geo at stat.math.ethz.ch
>> https://stat.ethz.ch/mailman/listinfo/r-sig-geo
>>     
>
>   
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