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I could use some guidance finishing a co-kriging script. I have rain
data, and elevation for each rain gauge. I have successfully make an
ordinary kriging of the rainfall. Now I'd like to try to use the
elevation as an auxiliary variable to improve the prediction. I have
made the model variogram with two variables, and the fitted
variogram using fit.lmc:<br>
<br>
vg.fit <- fit.lmc(vg, g, vgm(700, "Exp", 50000)) <br>
#gstat object 'g' prepared already with the 2 variables<br>
plot(vg, vg.fit) # (looks OK)<br>
<br>
then I run:<br>
# grd prepared in advance to match the range of the data<br>
precip.cokrige <- predict.gstat(vg.fit, newdata=grd) <br>
<br>
I expected to see:<br>
"Linear Model of Coregionalization.Good"<br>
[using ordinary cokriging]<br>
<br>
but instead the command returned:<br>
"Intrinsic Correlation found. Good.<br>
[using ordinary cokriging]"<br>
<br>
The co-kriging finishes successfully, and the results "look good."
But what am I getting? What is the difference between Intrinsic
Correlation and Linear Model of Coregionalization? <br>
<br>
Thanks,<br>
Micha<br>
<br>
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