Edzer, Ben, (I was missing the vignette on spatio-temporal analysis with gstat.. !!)
I'm attaching a clearer figure of the experimental variogram: the /origin/ at 0 spatio-temporal lag is not zero actually. Yes, I am using **variogramST** on a STFDF: the spacetime object looks ok, then I simply call: > variogramST(pm~1, mySTFDF, tlags=0:6) Ben, out of band I can give you my .Rdata cutout with the STFDF if you're interested. (It seems from the ST vignette that `variogramST` is now merged into `variogram` ?) -------------------------- > R.version.string [1] "R Under development (unstable) (2012-10-03 r60866)" -------------------------- Thanks, Piero On 15 January 2013 15:15, Benedikt Gräler <ben.grae...@uni-muenster.de>wrote: > Dear Piero, > > how did you compute these variograms, using variogramST in gstat (which > version?)? > > Figures 4-7 in gstat's vignette "Spatio-temporal geostatistics using > gstat" on CRAN show the missing value for the zero temporal and zero > spatial lag class. I could not identify this property in your wireframe > plots. > > To me, the temporal effect looks like being "upside-down". I'll be happy > to take a quick look at your script/data in case your problem still remains. > > Best, > > Ben > > > > > On 15.01.2013 11:51, Edzer Pebesma wrote: > >> Piero, >> >> from the orientation of your graph, I could not see very well what >> happens at zero-time, zero-space lag. >> >> Did you compute a pure-time variogram, i.e. with zero space distance? >> This one should have a missing zero-value, unless you have duplicate >> measurements. >> >> On 01/10/2013 03:20 PM, Piero Campalani wrote: >> >>> Dear list, >>> >>> I am predicting PM measurements on a spatiotemporal grid with monthly >>> intervals in time. >>> At modeling time, I am looking at the experimental 3D variograms >>> (`wireframes`) but I see that weird decreasing behavior in time (see >>> wireframes_2008-1.eps for January 2008): there is a peak at 0 time lags, >>> then correlation in time is much higher over different days. >>> How can I interpret such variogram? >>> Would it mean that there is a very high spatial variability for values on >>> the same day, whereas temporal variability is significantly lower? >>> >>> Thanks for any hint, >>> (I can provide implementation details in case of need) >>> >>> Piero >>> >>> >>> >>> ______________________________**_________________ >>> R-sig-Geo mailing list >>> R-sig-Geo@r-project.org >>> https://stat.ethz.ch/mailman/**listinfo/r-sig-geo<https://stat.ethz.ch/mailman/listinfo/r-sig-geo> >>> >>> >> > -- > Benedikt Gräler > > ifgi - Institute for Geoinformatics > University of Muenster > > http://ifgi.uni-muenster.de/**graeler<http://ifgi.uni-muenster.de/graeler> > > Phone: +49 251 83-33082 > Mail: ben.grae...@uni-muenster.de > > > ______________________________**_________________ > R-sig-Geo mailing list > R-sig-Geo@r-project.org > https://stat.ethz.ch/mailman/**listinfo/r-sig-geo<https://stat.ethz.ch/mailman/listinfo/r-sig-geo> >
wireframes_2008-1.eps
Description: PostScript document
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