Two main approaches to define the errors ε are implemented in SupraFit, (a) they are calculated from the standard normal distribution ε ∈ N(µ = 0, σ 2 ) or (b) randomly chosen from the absolute errors obtained after the successful fit (ε ∈ e). The later will be called bootstrapping (BS) in SupraFit and may be interpreted as a mixture of a typical Monte Carlo simulation and resampling technique. Bootstrapping is one of the resampling plans discussed by Efron. More recent discussions and problems using the bootstrapping method can be found in Canty et al. and in Efron and Hastie. The applied standard deviation σ MC in approach (a) can be taken from the SE y , σ f it or as manually defined value, where SE y is the default choice as proposed by Motulsky and Christopoulos since it is the corrected standard deviation (eq. 31). The 1 -2α confidence interval for each model parameter is then calculated using the percentile method: