I need to fit a complex function of a real variable to complex measured data. All algorithms I found so far assume real-valued data. Of course I could define an SSQ or chi^2 as usual and applay a general minimization algorithm, as e.g. Nelder-Mead Simplex. Buit I wonder if there are specialized, more efficient algorithms or even implementations of e.g. Levenberg-Marquardt?