JCNS :: Institutes
SANS: reduction, analysis, global instrumental fit
|“Simply Fit” Example:||fit-curve-introduction.pdf||cylinder-efit.fif||data-cylinder.qti|
Nonlinear curve fitting is an iterative procedure employing minimisation of the reduced chi-square value χ² to obtain the optimal parameter values. The reduced chi-square is obtained by dividing the residual sum of squares (RSS) by the degrees of freedom (DOF). Although this is the quantity that is minimized in the iteration process, this quantity is typically not a good measure to determine the goodness of fit. For example, if the y data is multiplied by a scaling factor, the reduced chi-square will be scaled as well.
M-Dimensional Data Sets [M>=1]
Residual Sum of Squares: