Fminsearch for fitting models (unconstrained nonlinear minimization of rmse)
4 visualizaciones (últimos 30 días)
Mostrar comentarios más antiguos
Wenquan
el 5 de Feb. de 2023
Comentada: Wenquan
el 5 de Feb. de 2023
Hi all, I'm trying to use the fminsearch function to fit a double sigmoidal models to my data. And the conditions is minimization of the root mean squared error(RMSE). I have seven parameters. At the moment, I'm using the following code.
load data
%xdata=Limb1_x; % 2424*1 vector
%ydata=Limb1_y; % 2424*1 vector
%type rmseval.mat
fun = @(v)rmseval(v,xdata,ydata);
v0= rand(1,7);
bestv = fminsearch(fun,v0);
a1=bestv(1);
a2=bestv(2);
b1=bestv(3);
b2=bestv(4);
c1=bestv(5);
c2=bestv(6);
d=bestv(7);
yfit=c1/(1+exp(-a1-b1*xdata))+c2/(1+exp(-a2-b2*xdata))+d;
figure;
plot(Limb1_x, Limb1_y, '+', 'MarkerSize', 10, 'LineWidth', 2)
hold on
plot(Limb1_x, yfit, '-')
function rmse = rmseval(v,xdata,ydata)
a1=v(1);
a2=v(2);
b1=v(3);
b2=v(4);
c1=v(5);
c2=v(6);
d=v(7);
rmse= sqrt(sum((ydata-(c1/(1+exp(-a1-b1.*xdata))+c2/(1+exp(-a2-b2.*xdata))+d).^2))/numel(xdata));
end
I don't have a good startpunkt. And the error is "Unable to perform assignment because the size of the left side is 1-by-1 and the size of the right sideis 1-by-2424." I'm quite a newbie in optimization. There is something I'm missing? And the data is in attachments.
Thank you in advance
0 comentarios
Respuesta aceptada
Matt J
el 5 de Feb. de 2023
rmse= sqrt(sum((ydata-(c1./(1+exp(-a1-b1.*xdata))+c2./(1+exp(-a2-b2.*xdata))+d).^2))./numel(xdata));
5 comentarios
Matt J
el 5 de Feb. de 2023
Editada: Matt J
el 5 de Feb. de 2023
I used trial and error. One of the advantages of fminspleas, however, if that you only need guesses for four of the parameters a1,b1,a2,b2. So, if you have any prior knowledge that can inform your guess of those, that might make things easier in future curve fittings.
Más respuestas (0)
Ver también
Categorías
Más información sobre Get Started with Curve Fitting Toolbox en Help Center y File Exchange.
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!