I think I've spent enough time trying to find a nice analytic way to guess parameters for a Gompertz model fit to my unfolding probability densities. I now have a heuristic which seems to work :p, and I suppose I'll be satisfied with that for the time being.

On to find out about analytic solutions to Kramers' unfolding rates.

Update: I figured out how to use the NIST reference while writing my sawsim paper, listing the mean and standard deviation of the Gumbel distribution. So many names… Anyway, the pysawsim tests now use the improved guessing procedure.