I'm pretty sure the Model Class is new to lmfit-py release 0.8.1 so you may have to update lmfit. (I have the offline documentation for 0.7.2 which does not include a section on the Model Class, but the documentation for version 0.8.1 has it)...

F stats and other associated methods for obtaining confidence intervals are far superior to a simple estimation of te co variance matrix for non-linear models (and others). The primary reason for this is the lack of assumptions about the Gaussian nature of error when using these methods. For non-linear systems,...

python,scipy,curve-fitting,lmfit

Hm, should that be out = mod1.fit(spectra_beBG[:,1], pars, x=spectra_beBG[:,0]) That is, you want to fit "y", and pass in the "pars" and "x" array to help calculate the model with those parameters and independent variables....

Because I don't have your data, I can't test it, but it looks like you're almost there. Your "gausfit2" should be a ModelFit object (http://cars9.uchicago.edu/software/python/lmfit/model.html#model.ModelFit). Therefore, all you would need to do to generate a report is the following: print gausfit2.fit_report #will print you a fit report from your model...