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Making GIS and R play nicely - some tips?

On Wed, 2 Mar 2005, abunn wrote:

            
What are the volumes going back?

Another itch to scratch is how much more you will get in terms of
precision in the coefficient point estimates by actually forcing all this
data down lm() or whatever's throat? Would it be possible to reduce the
load by using subsetting in rgdal, given that you had the *.img and model
based files lined up (or just use locations for which you have observed
climate data)?  Won't the interpolation errors in the predictors feed
through? I think the Furlanello et al. paper may be very helpful (they use
randomForest on regression trees of climate/topography drivers).

Interesting problem.

Roger