Fit: how to return chi-squared instead of r-squared

Hi, i'm performing this fit:

 f=fittype('a*(x^(-b))*exp(-x/c)');

 options = fitoptions('Method','NonlinearLeastSquares','StartPoint',[100,1,1]);

 [val1,val2,val3]=fit(x,y,f,options);

 disp(val2);

and I get on the screen

       sse: 9.7986e-04
       rsquare: 1.0000
       dfe: 97
       adjrsquare: 1.0000
       rmse: 0.0032

How could I get chi-square instead of r-square?

Answer 1

[Bruno Pop-Stefanov]

The Curve Fitting Toolbox only supports these goodness-of-fit statistics for parametric models:

• The sum of squares due to error (SSE)
• R-square
• Adjusted R-square
• Root mean squared error (RMSE)

If you want the chi-squared statistic, you will have to write your own code from your input data and your calculated fit.