deletions | additions       diff --git a/background-estimation.tex b/background-estimation.tex  index d857b2d..fa4b2cd 100644  --- a/background-estimation.tex  +++ b/background-estimation.tex 
...
The functions used to fit the background provide also a goodness-of-fit estimator   computed on the basis of the empirical distribution function (EDF)~\cite{Stephens1974,Parr1980}.   The ``distance'' between the EDF and the theoretical (i.e. exponential) cumulative distribution  represent represents  and indicator of the quality of fit. Two different distance metrics can be returned by the background fitting functions.  The first is the Kolgomorov-Smirnov statistics, which uses the maximum of the difference   between the EDF and the theoretical distribution. The second is the Cramér von Mises 
...
(see the code for more details,  \href{https://github.com/tritemio/FRETBursts/blob/master/fretbursts/background.py#L41}{link}).  In principle, the optimal interphoton-delay inter-photon delay  threshold will minimize the error metric. This approach is implemented by the function \verb|calc_bg_brute|  (\href{http://fretbursts.readthedocs.org/en/latest/plugins.html#fretbursts.burstlib\_ext.calc\_bg\_brute}{link}) which performs a brute-force search in order to find the optimal threshold.  This level of sofistication sophistication  in estimation estimating  the background rates is not necessary under typical circumstances, experimental conditions,  as the difference between an optimal threshold and a manually (or euristically) choosen heuristically) chosen  one is will be small if not  negligible in most practical cases.