fitting ODE solution to experimental data

[Peter Hinow]

Dear fellows,

is there a "canonical" way to fit the solution of a parameter-dependent ordinary differential equation y' = f(y;p) to some experimental data? 

I have tried leastsq, but the optimal solution is always the initial guess, regardless of the initial guess. Specifically, I'm not able to get any information why leastsq terminates, even when I add the option "imp=2" (the "optimal" gradient has an entry of order 10^21). When I try datafit instead, I get an error like

Submatrix incorrectly defined.
at line      26 of function costf called by :  
at line     174 of function datafit called by :  

even though the output of the objective function has the same size as the data vector.

Thank you very much for your help,
     Peter

-- 
Peter Hinow, PhD
Department of Mathematical Sciences
University of Wisconsin - Milwaukee
P.O. Box 413
Milwaukee, WI 53201-0413
USA
phone: ++1 414 229 4933
https://pantherfile.uwm.edu/hinow/www/