Poisson error bars for low count statistics, detection significances.
Project description
poissonregime
Poisson error bars for low count statistics, detection significances.
About
Low count statistics is not that hard. It’s just not Gaussian.
This package can answer the following questions:
Given k detected objects, what are the uncertainties on the true number of objects? (poissonregime.uncertainties_rate)
Given k “hits” out of a sample of n tries, what is the fraction and its uncertainty? (poissonregime.uncertainties_fraction)
What is the significance of k detections, given that I expect B background events? (poissonregime.significance) * what if I measure the background events from counts in a “off” region? * what if I have additional systematic uncertainty?
What is the probability distribution on the event rate, given a measured background rate? (poissonregime.posterior)
You can help by testing poissonregime and reporting issues. Code contributions are welcome. See the Contributing page.
Usage
Read the full documentation at:
Licence
MIT.
Other projects
See also:
Release Notes
0.1.0 (2021-06-11)
First version
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