[R-sig-Geo] Risks as hazardous (false positive) and safe (false negative)

[Zia Ahmed]

/Dear Edzer,
/
I am trying to do  misclassification following way: could you please 
tell me know whether  I am  statistically correct or wrong!

Thanks again
Zia/

# Load data
#-------------
tala<-read.csv("Tala_data.csv",header=TRUE)
tala.grid<-read.csv("Tala_grid_2.csv",header=TRUE)
# load packages:
#----------------
library(sp)
library(gstat)
library(lattice)
library(geoR)
library(MASS)
library(car)
coordinates(tala) <- ~ x + y       # Observed data
coordinates(tala.grid) <-~ x + y   # Prediction locations

# Box-cox transformation; required pakage- car
tala$was.bc<-box.cox(tala$was, .47)  # Power (lambda)= .47

# Varigram modeling:
#---------------------
v.ok<-variogram(was.bc~1,data=tala)
plot(v.ok, pl=F, pch=20, cex=1, col="Black")
m.ok<-vgm(.06,"Exp",4000,0.02)
(m.ok.f<-fit.variogram(v.ok, m.ok))
attr(m.ok.f,"SSErr") # Sum of Squared Error (SSE)

# Ordinary Kriging
#------------------

ok.was<-krige(was.bc~1,tala,tala.grid, model=m.ok.f, nmax=50)

# Back-and Indicator- transformation of OK prediction:
#-----------------------------------------------------------------------------------------
#Power=0.47
k<-1/0.47                                        
ok.was$was.bt <-((ok.was$var1.pred *0.47+1)^k)

target <- box.cox(0.100,0.47)
ok.was$was.target <- (ok.was$var1.pred>= target)
ok.was$p.target <- pt((-target +ok.was$var1.pred)/sqrt(ok.was$var1.var),
    length(tala$was.bc))
summary(ok.was)
coordinates(ok.was)<-~x+y

# Probability of true indicator
#-----------------------------------------------

plot(coordinates(ok.was), asp = 1, col = ifelse(ok.was$was.target,
"grey", "yellow"),//"Easting (m)", ylab="Northing (m)",//  main = 
"Probability of TRUE indicator",
sub = "Actual indicator: yellow/grey = FALSE/TRUE")
grid()

#-----------------------------------------------------------------
# Probability-of-exceeding 200 ppb ground water As conc.
#--------------------------------------------------------------------
levelplot(p.target~x+y| was.target, main="  (b) Probability > 0.200 mg 
As/L",
              xlab="Easting (m)", ylab="Northing (m)",
              as.data.frame(ok.was), aspect = "iso",at = seq(0, 1, by = 
0.05),
              col.regions=topo.colors,                            
              panel = function(...) {
              panel.levelplot(...)
              panel.abline(h = 0:4*5000 + 545000, v= 0:4*5000 + 2650000,
              col = "light grey")
},
     )

/
Edzer Pebesma wrote:
> (replying to the list)
>
> Well, if you're willing to accept the indicator kriging values as
> estimates of these probabilities, you're essentially done. Of course,
> the kriged values can be outside [0, 1], so you need to deal with that.
>
> Best regards,
> --
> Edzer
>
> Zia Ahmed wrote:
>   
>> Dear Edzer,
>>
>> Thanks for your replay. I have done IK of water arsenic using
>> quantiles of the data. I want to do   miss classification  of my risk
>> that  proposed  by  Goovaerts.
>> Two misclassification  of risks are proposed by Goovaerts (1997) based
>> on ccdf model F(*u*;z_k |(n)) of Z(*u*)?Z_k .
>>
>>
>> 1.       The risk ?(*u*) of incorrectly classified a location u as
>> hazardous (false positive):
>>
>> ?(*u*) = Prob{Z(*u*) ?z_c |z*_L (u) > Z_c , (n)}
>>
>>        = F(*u*;z_c |(n))
>>
>> Where z*_L (u) is the estimator.
>>
>> 2.       The risk ?(u)  wrongly classified a location u as safe (false
>> negative)
>>
>> ?(*u*) = Prob{Z(*u*) > z_c |z*_L (u) ? Z_c , (n)}
>>
>>       = 1- F(*u*;z_c |(n))
>>
>>
>>
>>
>>
>> Ref: Goovaerts, P (1997). Geostatistics for Natural Resource
>> Evaluation, pp: 259-368
>>
>>
>>
>> Zia
>>
>> Edzer Pebesma wrote:
>>     
>>> Dear Zia,
>>>
>>> If you mean by Goovaerts (1997) his 483 page book "Geostatistics for
>>> Natural Resource Evaluation", then please give us a bit more precise
>>> detail on what you want (which page? which equation?)
>>> -- 
>>> Edzer
>>>
>>> Zia Ahmed wrote:
>>>  
>>>       
>>>> Hi all,
>>>>
>>>> Is it possible in gstat to get misclassification  of risks as
>>>> hazardous (false positive) and safe (false negative) as describe by
>>>> Goovaerts (1997)  from parametric or non-parametric probability
>>>> mapping?.  help will appreciated.
>>>>
>>>> Thanks
>>>>
>>>> Zia
>>>>
>>>>
>>>>     
>>>>         
>>>   
>>>       
>
>