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 namesâ€¦ Anyway, the `pysawsim`

tests
now use the improved guessing procedure.