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I have to fit to experimental data a model function given by a linear combination of functions y1(t) and y2(t) 

        a1*y1(t) + a2*y2(t)

with a1 and a2 adjustable parameters.

The functions y1 and y2 are obtained by solving two coupled ODE's :

y1'(t)+y1(t)/t1-f(t)==0 with y1(0)==0

y2'(t)+y2(t)/t2-f(t)-a*y1(t)=0 with y2(0)==0

The function f(t) is known analytically.

Thus, there are 5 adjustable parameters a, a1, a2, t1, t2.

I found the following example in the Mathematica documentation, namely:

model[a_?NumberQ, b_?NumberQ, c_?NumberQ] :=  Module[{y, x},First[y /.NDSolve[{y''[x] + a y[x] == 0, y[0] == b, y'[0] == c}, 
 y, {x, 0, 10}]]]

nlm = NonlinearModelFit[data, model[a, b, c][x], {a, b, c}, x]

How can I generalize the given example to my case?

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    – Michael E2
    Commented May 14, 2015 at 14:22
  • $\begingroup$ Related: mathematica.stackexchange.com/questions/28461/… $\endgroup$
    – Michael E2
    Commented May 14, 2015 at 14:24
  • $\begingroup$ Post your data and the function f, please. $\endgroup$
    – Ivan
    Commented May 14, 2015 at 20:47

1 Answer 1

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paramSol = 
 ParametricNDSolve[{y1'[t] + y1[t]/t1 - f[t] == 0 , y1[0] == 0,
   y2'[t] + y2[t]/t2 - f[t] - a*y1[t] == 0 , y2[0] == 0}, {y1, 
   y2}, {t, 0, 10}, {a, t1, t2}];

model = Evaluate[a1 y1[a, t1, t2][t] + a2 y2[a, t1, t2][t] /. paramSol];


nlm = NonlinearModelFit[data, model, {a, a1, a2, t1, t2}, t]
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