Numeric least squares fit

Good evening to everybody,

I need some help in this fitting...

I have a collection of experimental data (texp, Iexp). Using these data, I generate a new collection of data, (texp, rteor), by solving a system of one equation per each couple of data, using fsolve with arrayfun:

    rteor= fsolve(@(r) arrayfun(@(R,T) FC.*integral(@(x) exp(-1./(30.*x.*log(x))), 1, R)-(T-t),r,texp), inpts);

(inpts=initial points; ). Then, I generate a new matrix of points, (texp, Iteor), evaluating the previous rteor data on a new function Iteor:

Iteor=rteor.*exp(a./(rteor(t).*log(rteor))) + (Io./(rteor(t).^4));

Well, now I want to fit this (Iteor, tteor) collection to (Iexp, texp) experimental collection by optimizing only the parameter "t" in the first "rteor" expression above. I would prefer to make it with a numerical method, not symbolic as the combination of

lsqcurvefit ( fsolve ( arrayfun ) )

, which I have already tried, takes a lot of time...

Hope anybody can help me. Thank you so much !!

//Sergio