[R-sig-Geo] variograms do not satisfy a legal model

[Edzer J. Pebesma]

Please try adding set in a call to create the gstat object:

g = gstat(... , set = list(nocheck = 1))
predict(g, newdata)
--
Edzer


ONKELINX, Thierry wrote:
> Edzer,
>
> Could you tell me how to override this check? I have been reading the
> helpfile but I can't find it.
>
> Thanks,
>
> Thierry
>
> ------------------------------------------------------------------------
> ----
> ir. Thierry Onkelinx
> Instituut voor natuur- en bosonderzoek / Reseach Institute for Nature
> and Forest
> Cel biometrie, methodologie en kwaliteitszorg / Section biometrics,
> methodology and quality assurance
> Gaverstraat 4
> 9500 Geraardsbergen
> Belgium
> tel. + 32 54/436 185
> Thierry.Onkelinx at inbo.be
> www.inbo.be 
>
> Do not put your faith in what statistics say until you have carefully
> considered what they do not say.  ~William W. Watt
> A statistical analysis, properly conducted, is a delicate dissection of
> uncertainties, a surgery of suppositions. ~M.J.Moroney
>
>  
>
>   
>> -----Oorspronkelijk bericht-----
>> Van: Edzer J. Pebesma [mailto:e.pebesma at geo.uu.nl] 
>> Verzonden: maandag 7 mei 2007 17:00
>> Aan: ONKELINX, Thierry
>> CC: r-sig-geo at stat.math.ethz.ch
>> Onderwerp: Re: [R-sig-Geo] variograms do not satisfy a legal model
>>
>> Thierry, you'll have to find out what the linear model of 
>> regionalization or intrinsic correlation mean; they are legal 
>> models, meaning that they lead to predictions with guaranteed 
>> non-negative prediction variances. There's a way to override 
>> the check (meaning it will not stop on error) but not to get 
>> that guarantee.
>> --
>> Edzer
>>
>> ONKELINX, Thierry wrote:
>>     
>>> Dear useRs,
>>>
>>> I'm trying to do some cokriging. I try fit the variograms 
>>>       
>> with fit.lmc 
>>     
>>> (gstat package).
>>>
>>> #Problem 1: how to get the model in an elegant way into the gstat 
>>> object? This is how I do it now.
>>> library("gstat")
>>> data(meuse)
>>> g <- gstat(id = "ln.zinc", formula = log(zinc)~1, locations = ~x+y, 
>>> data = meuse) g <- gstat(g, id = "ln.lead", formula = log(lead)~1, 
>>> locations = ~x+y, data = meuse) #fit the variogram models using 
>>> fit.lmc model <- fit.lmc(variogram(g), g, model = vgm(.55, 
>>>       
>> "Sph", 900, 
>>     
>>> .05), fit.ranges = FALSE) g <- gstat(g, id = "ln.zinc", model = 
>>> model[["model"]][["ln.zinc"]]) g <- gstat(g, id = 
>>>       
>> "ln.lead", model = 
>>     
>>> model[["model"]][["ln.lead"]]) g <- gstat(g, id = c("ln.zinc", 
>>> "ln.lead"), model =
>>> model[["model"]][["ln.zinc.ln.lead"]])
>>> predict(g, newdata = meuse)
>>>
>>> #Problem 2. the gstat object doesn't accept different 
>>>       
>> ranges. Or am I 
>>     
>>> doing something wrong?
>>> library("gstat")
>>> data(meuse)
>>> g <- gstat(id = "ln.zinc", formula = log(zinc)~1, locations = ~x+y, 
>>> data = meuse) g <- gstat(g, id = "ln.lead", formula = log(lead)~1, 
>>> locations = ~x+y, data = meuse) # examine variograms and cross 
>>> variogram:
>>> plot(variogram(g))
>>> # enter direct variograms:
>>> g <- gstat(g, id = "ln.zinc", model = vgm(.55, "Sph", 800, 
>>>       
>> .05)) g <- 
>>     
>>> gstat(g, id = "ln.lead", model = vgm(.55, "Sph", 900, .05)) # enter 
>>> cross variogram:
>>> g <- gstat(g, id = c("ln.zinc", "ln.lead"), model = vgm(.47, "Sph", 
>>> 900,
>>> .03))
>>> predict(g, newdata = meuse)
>>> # Error in predict.gstat(g, newdata = meuse) : gstat: value not 
>>> allowed
>>> for: variograms do not satisfy a legal model
>>>
>>> Thanks,
>>>
>>> Thierry
>>>
>>>
>>>       
>> ----------------------------------------------------------------------
>>     
>>> --
>>> ----
>>> ir. Thierry Onkelinx
>>> Instituut voor natuur- en bosonderzoek / Reseach Institute 
>>>       
>> for Nature 
>>     
>>> and Forest Cel biometrie, methodologie en kwaliteitszorg / Section 
>>> biometrics, methodology and quality assurance Gaverstraat 4 9500 
>>> Geraardsbergen Belgium tel. + 32 54/436 185 
>>>       
>> Thierry.Onkelinx at inbo.be 
>>     
>>> www.inbo.be
>>>
>>> Do not put your faith in what statistics say until you have 
>>>       
>> carefully 
>>     
>>> considered what they do not say.  ~William W. Watt A statistical 
>>> analysis, properly conducted, is a delicate dissection of 
>>> uncertainties, a surgery of suppositions. ~M.J.Moroney
>>>
>>> _______________________________________________
>>> R-sig-Geo mailing list
>>> R-sig-Geo at stat.math.ethz.ch
>>> https://stat.ethz.ch/mailman/listinfo/r-sig-geo
>>>   
>>>       
>>