Calculate residuals as a single number in lsqnonlin function
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I solve a nonlinear curve fitting problem using the lsqnonlin Matlab function.
I am interested to check the residual of my fitting each time so I am returning the residual each time I call the lsqnonlin function. I wanted to calculate a single number of the residual to see if the fits gets better after doing some changes in my data. My data are 3D images. Each time I calculated the sum of residuals using the sum() function. I ended up though with very large numbers, e.g. 7.3507e+04. Is there a better way to represent the residual in a single number than calculating the sum?
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Matt J
el 24 de Oct. de 2018
It is not clear why you think you need a "better" way. If you want the numbers to be smaller just scale down your objective function, e.g.,
objfun_new =@(x) objfun_old(x)/1e4;
Respuestas (2)
Rik
el 24 de Oct. de 2018
Yes, the sum of squares or the RMS:
SSq=sum(res.^2);
RMS=sqrt(mean(res.^2));
The downside of using the plain sum is that a large negative and a large positive will cancel out, which is clearly not what you want. Whether or not a number is large should not be a factor in your decision, just that you want to minimize it.
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Rik
el 30 de Oct. de 2018
Did this suggestion solve your problem? If so, please consider marking it as accepted answer. It will make it easier for other people with the same question to find an answer. If this didn't solve your question, please comment with what problems you are still having.
Torsten
el 24 de Oct. de 2018
If you use the usual naming conventions of lsqnonlin, the residual is "sum(F.^2)"
Best wishes
Torsten.
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