How to write a custom non linear function for data fitting?
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I wrote this script to fit some data with a custom nonlinear function, but I'm getting an almost flat line instead than an exponential.
myfittype=fittype('(N/(1 + exp((-N)*(b)*(t - tf))))','dependent',{'n'},'independent',{'t'},'coefficients',{'N','b','tf'});
h=fit(t,n,myfittype)
plot(h,t,n)
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the cyclist
el 23 de Mzo. de 2020
Editada: the cyclist
el 23 de Mzo. de 2020
I don't have the Curve Fitting Toolbox, so I can't really comment on your current code. But, if you also have the Statistics and Machine Learning Toolbox, you could try the fitnlm function.
% Some pretend data
t_data = (-2 : 0.1 : 10)';
f_data = 8 ./ (1 + exp(-2*(t_data - 5))) + 0.2*randn(size(t_data));
% Fitting function
f = @(F,t) F(1)./(1 + exp(-F(2).*(t - F(3))));
% Initial guess at parameters
beta0 = [1 1 1];
% Fit the model
mdl = fitnlm(t_data,f_data,f,beta0);
% Plot the fit against the data
figure
hold on
plot(t_data,f_data,'.')
plot(t_data,predict(mdl,t_data))
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John D'Errico
el 23 de Mzo. de 2020
Note that nonlinear fits often require an intelligent choice of starting values. The curvefitting toolbox uses random choice of initial values for general models if you give it nothing.
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