str(df)
`data.frame': 31837 obs. of 3 variables: $ x : num 410683 410700 410720 410740 410324 ... $ y : num 43136 43126 43123 43125 42709 ... $ wz: num -101.1 -94.9 -93.3 -94.5 30.8 ...
library(gstat)
g<-gstat(id="rv",form=wz~1,loc=~x+y,data=df,model=mat,nmax=500,set=list(average=1))
str(g)List of 3
$ data :List of 1
..$ rv:List of 10
.. ..$ formula :Class 'formula' length 3 wz ~ 1
.. .. .. ..- attr(*, ".Environment")=length 9 <environment>
.. ..$ locations :Class 'formula' length 2 ~x + y
.. .. .. ..- attr(*, ".Environment")=length 9 <environment>
.. ..$ data :`data.frame': 31837 obs. of 3 variables:
.. .. ..$ x : num [1:31837] 410683 410700 410720 410740 410324 ...
.. .. ..$ y : num [1:31837] 43136 43126 43123 43125 42709 ...
.. .. ..$ wz: num [1:31837] -101.1 -94.9 -93.3 -94.5 30.8 ...
.. ..$ has.intercept: int 1
.. ..$ beta : num(0)
.. ..$ nmax : num 500
.. ..$ maxdist : num Inf
.. ..$ dummy : logi FALSE
.. ..$ vfn : int 1
.. ..$ weights : NULL
$ model:List of 1
..$ rv:Classes variogram.model and `data.frame': 1 obs. of 9 variables:
.. ..$ model: Factor w/ 16 levels "Nug","Exp","Sph",..: 5
.. ..$ psill: num 1652
.. ..$ range: num 126
.. ..$ kappa: num 1.75
.. ..$ ang1 : num 0
.. ..$ ang2 : num 0
.. ..$ ang3 : num 0
.. ..$ anis1: num 1
.. ..$ anis2: num 1
.. ..- attr(*, "singular")= logi FALSE
$ set :List of 1
..$ average: num 1
- attr(*, "class")= chr [1:2] "gstat" "list"
str(new)
str(new) `data.frame': 580176 obs. of 3 variables: $ x : num 402292 402302 402312 402322 402332 ... $ y : num 43212 43212 43212 43212 43212 ... $ rok: num NA NA NA NA NA NA NA NA NA NA ...
k<-predict.gstat(g,new=new,mask=new$rok)Error in gstat.load.set(object$set) : error occured when parsing command: set average = 1;
If I do not set average=1 I continue getting the singular matrix error.
I see only one solution for this problem. That is o get rid if duplicate data in
some other way. As I am among the beginners in R and I do not speak other
programming languages either, I still did not find a successful way to krige
this data with a matern model varigram (which in my opinion suites best).
I also tried with the independent version of Gstat (2.4.2 if I remember
correctly) in combination with GRASS but seems that matern is not implemented in
it. Is that correct?
I am not a master of geostatistics either. Is there some other way to fit an S
shaped experimental variogram. Gaussian model would not fit that good, but at
least is an approximation.
thanks, Miha Staut
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