Question: How to calculate coefficient of determination of a nonlinear fit


The coefficient of determination also known as R^2 tells how good a fit is. If R^2=1 the fit is perfect an if R^2=0 it's useless. But Maple don't have a native function to calculate R^2. I seached and found this:

But it only describe how to calculate R^2 on a linear fit. I can understand from this:

"Users of linear regression models are accustomed to expressing the quality of fit of a model in terms of the coefficient of determination, also known as R2. In nonlinear regression, such a measure is unfortunately, not readily defined. One of the problems with the R2 definition is that it requires the presence of an intercept, which most nonlinear models do not have. A measure, relatively closely corresponding to R2 in the nonlinear case is Pseudo-R2 = 1 - SS(Residual)/SS(TotalCorrected)." source: a R2-Type Measure

That there is no real R^2 for non linear fits but there exist a Pseudo-R^2.

My question is: how do i calculate (Pseudo-)R^2 in a non-linear fit?


Also in excel there is an option to calculate R^2 on a non-linear fit:

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