Best tool to calculate the parameters of a custom equation fit
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Birsen Ayaz-Maierhafer
el 7 de Jul. de 2022
Hello,
There are quite a bit merhods/tools to fit an custom equation to the experimantal data. I am struggling to use the right one (I tried many of them and eventually decided to ask to an expert). My custom equation is (a+b/x^2)*exp(-x/c). What is the best way to find a,b and c if you really don't know what the starting parameter values are.
Thank you
Birsen
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Matt J
el 7 de Jul. de 2022
Editada: Matt J
el 7 de Jul. de 2022
For your particular equation, I'd rcommend,
[a,b,c]=deal(3,2,1)
x=linspace(1,2,30); %fake data
y=a+b./x.^2.*exp(-x/c);
funlist={1,@(c,x) exp(-x/c)./x.^2};
[c,ab]=fminspleas(funlist,2, x,y);
a=ab(1), b=ab(2),c %fitted values
yfit=a+b./x.^2.*exp(-x/c);
plot(x,y,'x',x,yfit); legend('Sample Data','Fit')
2 comentarios
Matt J
el 11 de Jul. de 2022
Editada: Matt J
el 14 de Jul. de 2022
Would it be the same with the updated equation?
I don't see any change in the equation since I posted. But yes, the fminspleas algorithm only iterates over c (and only requires an initial guess for c) in your case, because that is the only parameter that the model equation has a nonlinear dependence. on.
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Kevin Holly
el 7 de Jul. de 2022
Have you tried using the Curve Fitting Toolbox? You can fit your custom equation to a set of data and it will provide you with the coefficients that provide the best fit along with statistical metrics and a plot.
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