Successful _pΔMSE fits with equal SU start vector and stochastically varied elements. (A) Scheme of the stochastic variation of the start vector. SU start vectors extended over the range from 10⁻⁶ to 10³ yielding 19 SU vectors. The SU vectors were stochastically varied by the factor A = 10². 1,000 fits were performed for each SU start vector. The noise factor was 0.25 and 1,000 fits were performed for each SU vector. (B) After selection of successful_p fits, a second selection algorithm for fits was applied. Using the MSE_x values provided by the fit routine, the minimum MSE_x value, Min(MSE_x), was identified in the 1,000 fits and the difference of each MSE_x to the Min(MSE_x) was calculated, yielding ΔMSE_x. ΔMSE_x values were sorted, starting with the smallest, and plotted for x > 0 on a logarithmic scale. A threshold was set at 10⁻¹⁰ (red dashed lines) to identify all fits in close proximity of ΔMSE₁ = 0. All values below 10⁻¹⁰ indicate successful_pΔMSE fits. For all four models, the sums of all obtained successful_pΔMSE fits out of 19,000 fits are indicated.