Programmatically calculate goodness of fit using Curve Fitting Toolbox?
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Hi,
I am hoping to retrieve the goodness of fit values that the curve fit tool calculates for a custom model, but programatically. My model is:
g=fittype('a*sin(2*pi*25000000*x+b)+c')
which I fit to x and y data with:
f=fit(x,v,g)
(where v is for voltage). This returns the following:
f =
General model:
f(x) = a*sin(2*pi*25000000*x+b)+c
Coefficients (with 95% confidence bounds):
a = -13.03 (-13.04, -13.02)
b = -4.746 (-4.747, -4.745)
c = -0.3985 (-0.4073, -0.3897)
From here I want to see the sum of squares due to error (SSE), R-square, Adjusted R-square, and Root Mean Square Error (RMSE), as a quantitative assessment of the model quality. Does anyone have any solutions? There is no obvious way of retrieving this information listed in the documentation for the toolbox.
Thanks in advance.
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Accepted Answer
Matt J
on 8 Feb 2014
The FIT command returns goodness of fit info as its second output argument, as documented here
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