deletions | additions       diff --git a/res_fitfunction.md b/res_fitfunction.md  index 2303991..6dcd443 100644  --- a/res_fitfunction.md  +++ b/res_fitfunction.md 
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\[  F_i(t) = b(\mathbf{q}_i, t)+ \sum_{k=0}^{m} f(\mathbf{r}_{i,k},t) + W + R  \]  , where \(b\) is a n-th order polynomial with \(\mathbf{q}_i\) being the polynomial coefficients for the *i*-th pixel, summation is performed over all *m* events in the pixel, \(W\) represents noise and \(R\) is the remaining residual not captured in the baseline nor events. Ideally, \(R=0\), but achieving this is limited by the accuracy of the event region detection (we cannot fit what we do not detect) and whether or not our fitting function is general enough to be able to approximate various types of events. Because it is not know which part of the signal is the event and which is the baseline the first fit also has to estimate the baseline properties.  Signal in the candidate region is fitted with an extended fit function (Figure \ref{fig:fit}) that also depends on relaxation baseline \(B\) and baseline offset \(C\). The \(C\) parameter allows for the possibility of an elevated background before the release event.