How to do parameter fitting for a system of equations with 3 independent variables?

I have a system of 3 equations with 3 independent variables( x1,x2,x3) and correspondingly 3 dependent variables( y1,y2,y3) as follows:
  • y1=((b1*x1)/(1+(b1*x1)+(b2*x2)+(b3*x3))) + ((b4*x1)/(1+(b1*x1)+(b2*x2)+(b3*x3)));
  • y2=((b2*x2)/(1+(b1*x1)+(b2*x2)+(b3*x3))) + ((b5*x2)/(1+(b1*x1)+(b2*x2)+(b3*x3)));
  • y3=((b3*x3)/(1+(b1*x1)+(b2*x2)+(b3*x3))) + ((b6*x3)/(1+(b1*x1)+(b2*x2)+(b3*x3)));
x and y data are available.
I need to fit 6 parameters( b1,b2,b3,b4,b5,b6) in this system.
I tried using nlinfit but couldn't make it work for this case. Suggest me how to solve this problem. Thank you.

 Respuesta aceptada

Torsten
Torsten el 18 de Ag. de 2015
Editada: Torsten el 18 de Ag. de 2015
xdata = horzcat(x1,x2,x3);
ydata = horzcat(y1,y2,y3);
fun=@(b,xdata) horzcat((b(1)+b(4))*x1./(1+b(1)*x1+b(2)*x2+b(3)*x3),(b(2)+b(5))*x2./(1+b(1)*x1+b(2)*x2+b(3)*x3),(b(3)+b(6))*x3./(1+b(1)*x1+b(2)*x2+b(3)*x3));
b0=[1 ; 1 ; 1 ; 1 ; 1 ; 1];
[x,resnorm] = lsqcurvefit(fun,b0,xdata,ydata);
Best wishes
Torsten.

1 comentario

I tried doing this on a similar problem and the extimated x output changes with the initial guess, even when setting a very low tolerance:
% code
opts = optimset('TolX',1e-15);
[vestimated,resnorm] = lsqcurvefit(fun,x0,xdata,ydata,[],[],opts);%
how does lsqcurvefit pass x1,x2 and x3 into fun?, shouldn't fun be expressed in terms of
xdata(initial_index:final_index).
rather than in terms of x1,x2 and x3?
Thanks

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el 18 de Ag. de 2015

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el 25 de Mayo de 2017

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