I wonder if there is an easy way to calculate model-dependent fit statistics such as reduced $\chi^2$ values, for example. $\chi^2_\nu = \chi^2 / \text{d.o.f.}$ where the $\chi^2$ value is derived from the data and the fit (model folded through response), and the number of degree of freedom (d.of.) is equal to $(\text{number of data bins}) - (\text{number of free parameters})$ which come from the data and model, respectively.