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

[Edzer Pebesma]

Zia Ahmed wrote:
> /Dear Edzer,
> /
> I am trying to do  misclassification following way: could you please
> tell me know whether  I am  statistically correct or wrong!
Zia, to do this, I would need your data, a lot of information about your
data, and a lot of time. And then, the answer would be a long one and
not one in the sense of "yes" or "no". I'm sorry, but you either
overestimate my capabilities, or those of statistical methods in
general, or both!
>
> 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
>>>>>
>>>>>
>>>>>             
>>>>         
>>
>>   
>

-- 
Edzer Pebesma
Institute for Geoinformatics (ifgi), University of Münster
Weseler Straße 253, 48151 Münster, Germany. Phone: +49 251
8333081, Fax: +49 251 8339763 http://ifgi.uni-muenster.de/
http://www.springer.com/978-0-387-78170-9 e.pebesma at wwu.de