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Starting with an initial set of parameters, the algorithm evaluated the fit produced by 80 adjacent parameter sets (see Supporting Information for additional details), retained the set that produced the best fit (smallest sum of squared differentials), and repeated the process starting over with the retained best-fit parameters.
Similar(59)
Return the sum of squared element values.
Derivations from maximum likelihood estimation, maximizing the variance, and minimizing the sum of squared projection errors.
sum of squared residuals.
(Sum of squared logarithms inequality).
Fig. 7 Cumulative sum of squared differences.
(Sum of squared logarithms inequality for (n=4)).
Nevertheless, the sum of squared logarithms inequality holds.
SSD: sum of squared deviations.
The sum of squared variation of social relationships is 948170.290.
As similarity metric we used the sum of squared differences.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com