significance¶
-
gammapy.stats.
significance
(n_on, mu_bkg, method='lima', n_on_min=1)[source]¶ Compute significance for an observed number of counts and known background.
The default
method="lima"
gives the significance estimate corresponding to equation (17) from the Li & Ma paper [1] in the limiting of known background \(\mu_{bkg} = \alpha \times n_{off}\) with \(\alpha \to 0\).It is given by the following formula:
\[S_{lima} = \sqrt{2} \left[ n_{on} \log \left( \frac{n_{on}}{\mu_{bkg}} \right) - n_{on} + \mu_{bkg} \right] ^ {1/2}\]For
method="simple"
, the significance estimate is given by:\[S_{simple} = (n_{on} - \mu_{bkg}) / \sqrt{\mu_{bkg}}\]- Parameters
- n_onarray_like
Observed number of counts
- mu_bkgarray_like
Known background level
- method{“lima”, “simple”}
Method for significance estimation
- n_on_minfloat
Minimum
n_on
(returnNaN
for smaller values)
- Returns
- significance
ndarray
Significance estimate
- significance
See also
References
Examples
>>> significance(n_on=10, mu_bkg=2, method='lima') 4.0235256 >>> significance(n_on=10, mu_bkg=2, method='simple') 5.65685425