Weird experimental 3D spatiotemporal variogram

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 Gr?ler <ben.graeler at 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

--
Benedikt Gr?ler

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.graeler at uni-muenster.de