Hello all,
I'm using Gstat/R for regression kriging. I don't have values for all locations
in the predictor variables for which I want to interpolate a surface. I do
however want to make use of the independent predictors. Therfor I combined
regression kriging with ordinary kriging:
1. regression kriging: krige(log(cer+1) ~ pred1 + pred2 , data,
data.pred.grid, model = vgm.fit1)
2. ordinary kriging: krige(log(cer+1) ~ 1, data,
pred.grid, model = vgm.fit0)
3. add the values from the second step to the grid where the first step gives
NA:
s0 = [EMAIL PROTECTED]
s1 = [EMAIL PROTECTED]
s1[is.na(s1)] <- 0 # make the NA zero
s0[!is.na(s1)] <- 0 # make everyting that is not NA in s1 zero
s1 = s1 + s0 # now, all locations get a predicted value despite
missing predictors
[EMAIL PROTECTED] = s1
Is this ok, or should I interpolate (in fact, extrapolate) the predictors to
get values at all necessary locations instead? Better solutions available?
Thank you in advance for time and effort.
Best regards,
Eelke
Eelke Folmer
Animal Ecology Group
University of Groningen
P. O. Box 14
9750 AA Haren
The Netherlands
+31(0)50 3632091
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