Include sign in TS definition
@@ -18,11 +18,13 @@ energy.
The core of any estimator algorithm is hypothesis testing: a reference
model or counts excess is tested against a null hypothesis. From the
-best fit reference model a flux is derived and a corresponding :math:`\sqrt{\Delta TS}`
+best fit reference model a flux is derived and a corresponding :math:`\Delta TS`
value from the difference in fit statistics to the null hypothesis.
Assuming one degree of freedom, :math:`\sqrt{\Delta TS}` represents an
approximation (`Wilk's theorem <https://en.wikipedia.org/wiki/Wilks%27_theorem>`_)
-of the "classical significance".
+of the "classical significance". In case of a negative best fit flux,
+e.g. when the background is overestimated, the significance is defined
+as :math:`-\sqrt{\Delta TS}` by convention.
In general the flux can be estimated using methods:
@@ -53,7 +55,7 @@ e_max Maximum energy
norm Best fit norm with respect to the reference spectral model
norm_err Symmetric error on the norm derived from the Hessian matrix
ts Difference in fit statistics (`stat - stat_null` )
-sqrt_ts Square root of ts, in case of one degree of freedom, corresponds to significance (Wilk's theorem)
+sqrt_ts Square root of ts time sign(norm), in case of one degree of freedom, corresponds to significance (Wilk's theorem)
================= =================================================
@@ -70,7 +72,7 @@ stat_null Fit statistics value of the null hypothesis
================= =================================================
npred Predicted counts of the best fit hypothesis
npred_null Predicted counts of the null hypothesis
-npred_signal Predicted counts of the signal over `npred_null`, equivalent to (`npred - npred_null`)
+npred_excess Predicted counts of the excess over `npred_null`, equivalent to (`npred - npred_null`)
================= =================================================
norm_scan Norm scan
stat_scan Fit statistics scan
