Dear Gerard,
Thank you very much for the quick answer. I am a bit uncertain, what you
meant by total frequency of type A. I have data on the extent of type A at a
location (let's call it freqA), this can be taken for fequency, yes and I
have information on the total extent of all the nautral vege
Quick response on the binomial:
If possible I would suggest you should model
pi = (number/freq of type A) / (total_freq of type A)
veg.glm = glm ( pi ~ x, weights = total_freq, family=binomial)
The glm method is supposed to work only on the natural numbers (inc 0!) but
also works for decimal da
Dear experts of boosting!
I am planning to build vegetation models via boosting with either gbm or
mboost. My problem is that my response variable is the proportion of a
vegetation type in natural vegetation at a location.
ResponseA = (area of vegetation type A/area of all natural vegetation ty
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