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I implemented the nuiscance parameter "logf" in the lnprob function within measure_extinction/utils/fit_model.py following the emcee docs here (https://emcee.readthedocs.io/en/stable/tutorials/line/). This enables the fitting to take some steps toward addressing if the error bars are underestimated. To do this I converted the existing 'self.weights' back into a numpy array of errors before summing them with the model and logf as required.
I also added "logf" to the params list as the final element to assist in propagating the new parameter through the code.