GSTAT: Optimize power value for IDW

Zev Ross schreef:

Hi All,

ArcGIS has a nice little button that calculates the optimal power 
value to use for inverse distance weighting based on cross-validation 
and RMSPE. Just wondering if anyone had written something similar in R 
-- I'm using GSTAT and I'd like to avoid back and forth with ArcGIS 
(and obviously I'd like to avoid writing it myself as well!).

Zev

Hi,

I don't have any code lying around, but a brute force optimization 
approach should be quite easy. Also because the range of idw-powers is 
relatively small. The speed would ofcourse depend on the size of the 
dataset. In code it would look something like (actually works :)):

library(gstat)
data(meuse)
coordinates(meuse) = ~x+y

# make function to do the cv
do_cv = function(idp) {
  meuse_idw = gstat(id = "zn", formula = zinc~1, data = meuse, set = 
list(idp = idp))
  out = gstat.cv(meuse_idw)
  return(sqrt(mean(out$residual^2))) # RMSE as optimization criterium
}

idw_pow = seq(0.1,5, by = 0.2) # the idwpower values that will be checked
cv_vals = sapply(idw_pow, do_cv) # calculate the rmse
# List of outcomes
print(data.frame(idp = idw_pow, cv_rmse = cv_vals))

After this you select the idw value with the smallest RMSE.

cheers and hth,
Paul

Drs. Paul Hiemstra
Department of Physical Geography
Faculty of Geosciences
University of Utrecht
Heidelberglaan 2
P.O. Box 80.115
3508 TC Utrecht
Phone:     +31302535773
Fax:    +31302531145
http://intamap.geo.uu.nl/~paul