Inferring the success parameter p
of a binomial model
from small samples affected by background
The problem of inferring the binomial parameter p
from x successes obtained in n trials
is reviewed and extended to take into account the presence
of background, that can affect
the data in two ways: a) fake successes are due to
a background modeled as a Poisson process of known intensity;
b) fake trials are due to
a background modeled as a Poisson process of known intensity,
each trial being characterized by a known
success probability pb.
Reference to this paper: physics/0412069
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