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docs: Clarify staterror modifier specification #1856

Merged
merged 12 commits into from
May 24, 2022
1 change: 1 addition & 0 deletions docs/contributors.rst
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Expand Up @@ -27,3 +27,4 @@ Contributors include:
- Mason Proffitt
- Lars Henkelmann
- Aryan Roy
- Jerry Ling
20 changes: 12 additions & 8 deletions docs/likelihood.rst
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Expand Up @@ -194,16 +194,20 @@ MC Statistical Uncertainty (staterror)

As the sample counts are often derived from Monte Carlo (MC) datasets, they
necessarily carry an uncertainty due to the finite sample size of the datasets.
As explained in detail in :cite:`likelihood-Cranmer:1456844`, adding uncertainties for
As explained in detail in :cite:`likelihood-Cranmer:1456844`, adding uncertainties for
each sample would yield a very large number of nuisance parameters with limited
utility. Therefore a set of bin-wise scale factors :math:`\gamma_b` is
utility.
Therefore a set of bin-wise scale factors :math:`\gamma_{cb}` is
introduced to model the overall uncertainty in the bin due to MC statistics.
The constraint term is constructed as a set of Gaussian constraints with a
central value equal to unity for each bin in the channel. The scales
:math:`\sigma_b` of the constraint are computed from the individual
uncertainties of samples defined within the channel relative to the total event
rate of all samples: :math:`\delta_{csb} = \sigma_{csb}/\sum_s \nu^0_{scb}`. As
not all samples are within a channel are estimated from MC simulations, only
The constraint term is constructed as a set of constraints with a
central value equal to unity, e.g. :math:`\mathrm{Gauss} (\mu = 1, \sigma_{cb})`, for
each bin in the channel.
The scales :math:`\sigma_{cb}` of the constraints are computed from the individual
uncertainties of samples defined within the channel relative to the total event rate
of all samples: :math:`\sigma_{cb} = \sqrt{\sum_s\delta_{csb}}/\sum_s \nu^0_{csb}`,
where :math:`\delta_{csb}` is the absolute yield uncertainty in each bin.

As not all samples within a channel are estimated from MC simulations, only
the samples with a declared statistical uncertainty modifier enter the sum.
An example of a statistical uncertainty modifier for a single bin channel is
shown below:
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