deletions | additions       diff --git a/Burst_Weights_Theory.tex b/Burst_Weights_Theory.tex  index 70de7ff..4c6d8fa 100644  --- a/Burst_Weights_Theory.tex  +++ b/Burst_Weights_Theory.tex 
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\subsubsection{Weighted FRET estimator}  Here we report a simple verification of the results of previous section, namely  that a weighted mean of $E_i$ is the estimator with minimal variance of $E_p$.  For this purpose, we generated a static FRET population of 200 100  bursts by simply extracting burst-sizes from an exponential distribution ($\lambda = 50$) 10$)  and acceptor counts from a binomial distribution ($E_p = 0.2$).   By repeatedly fitting the population parameter $E_p$ using a   size-weighted and unweighted average, we verified that the former has systematically  lower variance of the latter as predicted by the theory. Note that this result  holds for any arbitrary distribution of burst sizes. The full simulation including exponential and gamma-distributed burst sizes  is reported in the accompanying Jupyter notebook (\href{}{link}).  \subsubsection{Weighted FRET histogram}