I was hoping people could offer me some advice - sorry in advance if this is a stupid question.
I am fitting a 2D function to some Monte Carlo samples using an unbinned likelihood fit with RooFit. The fits are looking good and converging nicely however, I would like a measure of just how good the fit is.
I thought I could use the Kolmogorov-Smirnov test, but that appears to be for 1D functions only.
I know I could do just find the chi^2 but that would mean binning everything - and I would rather not bin my data unless absolutely necessary.
Is there any standard way of evaluating a 2D unbinned fit?