spey.ExpectationType

class spey.ExpectationType(value, names=None, *, module=None, qualname=None, type=None, start=1, boundary=None)

Expectation type has been used to determine the nature of the statistical model through out the package. It consists of three main arguments:

• observed : indicates that the fit of the statistical model will be done over experimental data

• aposteriori: as in observed the fit will be done over data where the likelihood results will be identical to observed, computation of \(CL_s\) values will be done for by centralising the test statistics around background.

• apriori: theorists are generatly interested in difference of their model from the SM simulation. Hence this option will overwrite the observed data in the statistical model with simulated background values and performs the computation with respect to prefit values, meaning prior to the experimental observation. \(CL_s\) values are again computed by centralising the test statistics around the background i.e. SM background.

User can simply set the value of expected to a desired ExpectationType:

>>> expected = spey.ExpectationType.aposteriori

This will trigger appropriate action to be taken through out the package.

__init__(*args, **kwds)

Attributes

apriori
aposteriori
observed