[R-sig-Geo] Spatio Temporal kriging in Gstat

Benedikt Graeler benedikt.graeler at rub.de
Thu Jun 23 09:54:34 CEST 2016 

Dear Dan,

the error occurs because your prior.stvgm is far from the structure of 
your data. The following model provides better starting values:

prior.stvgm=vgmST(stModel="sumMetric",
                         space=vgm(0.1,"Exp",0.5,0.3),
                         time=vgm(0.1,"Exp",0.5,0.3),
                         joint=vgm(0.1,"Exp",0.5,0.3),
                         stAni=1)

To get a first "estimate", it is always useful to look at a plot of the 
sample variogram (as in the spatial case):

plot(sample.stvgm, wireframe=T, scales=list(arrows=F))

 From the plot, one can read spatial and temporal ranges, the magnitude 
of variability and the ratios of nuggets and sills. Sometimes, one is 
better of by starting with a simpler model (e.g. "pure" metric), as the 
routines are more robust for less parameters, to get a first impression 
of the range of parameters. Furthermore, the plot suggests that a much 
smaller spatial upper boundary is sufficient, as the variogram surface 
is mainly flat in the spatial dimension.

Spatio-temporal geostatistics remains tricky in terms of numerical 
routines and model interpretation, we try to give some guidance 
regarding gstat's functionalities in [1].

HTH,

  Ben

[1] https://journal.r-project.org/archive/accepted/na-pebesma-heuvelink.pdf


On 21.06.2016 17:16, Dan Turenne wrote:
> Hello again,
>
>
> After some tinkering with my code last night I got the sample variogram to work however now I have encountered another issue.  When attempting to use the fit.stVariogram function to fit the sample variogram I receive this error:
>
>
> Error in optim(extractPar(model), fitFun, ..., method = method, lower = lower,  :
>   non-finite value supplied by optim
>
>
> even if I specify the upper and lower arguments to be finite.  Could this error be cause by the initial values that I set for the space, time and joint variograms?  If so can anyone recommend  a good paper/article about how to fit these three variograms?  I have attached a link to my script and data below, if anyone has any insight as to why I am getting this error it would be appreciated.  I tried to be as thorough as I could in my code commenting, please let me know if anything is unclear.
>
>
> https://www.dropbox.com/sh/7ccy5wu68gxf6sf/AACmk0AFxQvetunq4YPc9DXla?dl=0
>
>
> ________________________________
> From: R-sig-Geo <r-sig-geo-bounces at r-project.org> on behalf of Edzer Pebesma <edzer.pebesma at uni-muenster.de>
> Sent: June 21, 2016 1:52 AM
> To: r-sig-geo at r-project.org
> Subject: Re: [R-sig-Geo] Spatio Temporal kriging in Gstat
>
> This might be due to a bug (or feature) in the software caused by the
> sparseness in your data, which might be different from that used to test
> the software. Please make the data available (off-list), along with an R
> script, so we can try to reproduce the error message and look into it.
>
> On 21/06/16 04:11, Dan Turenne wrote:
>> My apologies, I accidentally sent an unfinished email, here is the complete version of my question
>>
>>
>> Hello R-Sig-Geo,
>>
>>
>> As part of my masters thesis I am attempting to use spatio-temporal regression kriging to make predictions with temperature data, and I was hoping that someone might be able to give some insight as to how the algorithms work in gstat.  My data consists of daily temperature observations from April 1 to July 31, 2000.  There are observations from 164 stations across these 122 days, however not all stations have observations on all days, making for a total of 19282 records.
>>
>>
>> I have tried to use an STSDF object but I have not had any success.  I created an sp object of length 164 with the station locations:
>>
>>
>>     sp = data.frame(long = stations$long, lat = stations$lat)
>>
>>     coordinates(sp) = ~ long+lat
>>
>>
>> Then I created a vector of length 122 with the times the observations were recorded and a data vector of length 19282:
>>
>>
>>     beginDate = as.Date(2000/04/01)
>>
>>     endDate = as.Date(2000/07/31)
>>
>>     times = as.POSIXct(seq(beginDate,endDate,by="days"))
>>
>>
>>     data=data.frame(temps$residual)
>>
>>
>> And I also made an index detailing where observations are available, it looks like this with the first column representing spatial index and the second representing the time index
>>
>>
>>     1   1
>>
>>     2   1
>>
>>     3   1
>>
>>     4   1
>>
>>
>>     st=STSDF(sp,time,data,index,endTime=delta(time))
>>
>>
>> however when I try to calculate the sample variogram I get the following error:
>>
>>
>>     sample.stVariogram=variogramST(residual~1,data=st, tunit="days", tlags=1:7, progress=TRUE)
>>
>>
>>
>>    Error in apply(do.call(cbind, lapply(ret, function(x) x$np)), 1, sum,  :
>>    dim(X) must have a positive length
>>    In addition: There were 50 or more warnings (use warnings() to see the first 50)
>>
>>
>> All 50 of the errors are :
>>
>>
>>   In is.na(data[[as.character(as.list(formula)[[2]])]]) :
>>    is.na() applied to non-(list or vector) of type 'NULL'
>>
>>
>> Can anyone see what I am doing wrong or give me any pointers?  This error  is rather cryptic and I'm not quite sure what I'm doing wrong.  Any help would be appreciated.
>>
>>
>> Many Thanks,
>>
>> Daniel Turenne
>>
>> University of Manitoba
>>
>>
>>        [[alternative HTML version deleted]]
>>
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>>
>
> --
> Edzer Pebesma
> Institute for Geoinformatics  (ifgi),  University of M�nster
> Heisenbergstra�e 2, 48149 M�nster, Germany; +49 251 83 33081
> Journal of Statistical Software:   http://www.jstatsoft.org/
> Computers & Geosciences:   http://elsevier.com/locate/cageo/
> Spatial Statistics Society http://www.spatialstatistics.info
>
>
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-- 
Dr. Benedikt Gräler
Institute of Hydrology
Ruhr University Bochum
Universitätsstraße 150
44801 Bochum

ben.graeler.org

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