Hi all,
I am trying to simulate a locally gaussian field using gstat. The command
file looks like this:
#
# Strates: 0=Sud 1=Nord 2=Voie navigable
#
data(HG0): 'Hg89Export.txt', x=4, y=3, v=5, log, max=12, min=3, radius=3000,
b=[0] ;
data(HG1): 'Hg89Export.txt', x=4, y=3, v=5, log, max=12, min=3, radius=3000,
b=[0] ;
data(HG2): 'Hg89Export.txt', x=4, y=3, v=5, log, max=12, min=3, radius=3000,
b=[0] ;
data(): 'GrilleLSF.txt', x=1, y=2, s=3 ;
variogram(HG0): .2 Exp(3266) ;
variogram(HG1): .5 Exp(3266) ;
variogram(HG2): .35 Exp(3266) ;
method: gs;
set output='pr89sim.out';
set nsim=50;
The prediction file contains 1531 positions located on a square grid
covering a lake divided in three strata (North shore, South shore and center
channel). The output has the following strange characteristic: The
variability of predicted values at a given prediction location depends on
its order in the file. In the original GrilleLSF.txt file, the prediction
locations go from west to east, south to north. The standard deviation of
predicted values, depicted here as the size of the circles, looks like this:
Notice the sudden increase in variability around x=544000 which, given the
conditioning data, is rather unexpected. When the order of the file is
reversed, everything else kept the same, the variability of simulated values
becomes :
Now the most variable section is in the west, up to x=551000. It is as if
the first, maybe 500, points in the data() file were not treated the same as
the rest. What might cause this?
I hope the figures make it througt the list server.
Thanks in advance.
Pierre Gagnon
Centre Saint-Laurent
105 McGill, Montréal
(Québec) H2Y 2E7
514 496 1456
http://www.qc.ec.gc.ca/csl/ <http://www.qc.ec.gc.ca/csl/>