I would like to know how R computes the probability of an event in a
logistic model (P(y=1)) from the score s, linear combination of x and
beta.
I noticed that there are differences (small, less than e-16) between the
fitting values automatically computed in the glm procedure by R, and the
values "manually" computed by me applying the reverse formula
p=e^s/(1+e^s); moreover I noticed that the minimum value of the fitting
values in my estimation is 2.220446e-16, and there are many observation
with this probability (instead the minimum value obtained by "manually"
estimation is 2.872636e-152).
Fabrizio Renzi
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