Hey all,

I need some help with a cross validation. I'm new with R and as well with
statistics. I had a group work to create a tool for remote sensing class
that extracts the best bands of hyperspectral satellite images that describe
vegetation. Its a regression between a linear function of using a normalized
differenced index (i-j)/(i+j) while i and j are the bands (in the data these
are the columns, expect the last column) and the ground truth data which is
listed in the last column in %.
We did a manual cross validation (described below), but as the code is too
long and confusing, we'd like to use the cv.glm function out of the boot
package. We've tried it several times, but we don't know how to do ist.
Could anybody help us? 
This is our current code for the tool with a manual cross validation:


Thanks a lot,
Motte

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