Hi Jin,
Which differences do you exactly refer to? I'd say that what happens in
demo(cokriging) is ordinary cokriging. As it says:
...
[using ordinary cokriging]
Best regards,
--
Edzer
[EMAIL PROTECTED] wrote:
Hi All,
I am going to compare a few spatial interpolation techniques including
kriging with an external drift (KED) and ordinary co-kriging (OCK) (such as
those defined in: Goovaerts, 1997. Geostatistics for Natural Resources
Evaluation.) to interpolate marine sediment data (mud content in this case)
using bathymetry as a secondary variable. However, it seems that the ordinary
cokriging in gstat as shown in demo(cokriging) is different from the OCK we
planned to use. Is it possible to do such OCK in gstat? Any comments and
example? Thanks.
As to KED, I tried
vgm1 <- variogram(sqrt(mud)~bathy, data.file.dev)
model.1 <- fit.variogram(vgm1,vgm(1,"Sph",5,1))
# plot(vgm1, model.1)
coordinates(data.file.pred) = ~LON+LAT
mud.ok <- krige(sqrt(mud)~bathy, data.file.dev, data.file.pred, model =
model.1)
[using universal kriging]
vgm1 <- variogram(sqrt(mud)~LON+LAT, data.file.dev)
model.1 <- fit.variogram(vgm1,vgm(1,"Sph",5,1))
# plot(vgm1, model.1)
coordinates(data.file.pred) = ~LON+LAT
mud.ok <- krige(sqrt(mud)~LON+LAT, data.file.dev, data.file.pred, model =
model.1)
[using universal kriging]
Both of them are UK. But the first one seems regression kriging. Is it
identical to KED in this case? If not, any comments and examples of KED are
appreciated.
Cheers,
Jin
--------------------------------------------
Jin Li, PhD
Spatial Modeller/
Computational Statistician
Marine & Coastal Environment
Geoscience Australia
Ph: 61 (02) 6249 9899
Fax: 61 (02) 6249 9956
email: [EMAIL PROTECTED] <mailto:[EMAIL PROTECTED]>
--------------------------------------------
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--
Edzer Pebesma
Institute for Geoinformatics (ifgi), University of Münster,
Weseler Straße 253, 48151 Münster, Germany. Phone: +49 251
8333081, Fax: +49 251 8339763 http://ifgi.uni-muenster.de/
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