[[!meta  title="Giving up on Gompertz theory"]]
[[!meta  date="2008-06-30 21:22:51"]]
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][guess].

[NIST reference]: http://www.itl.nist.gov/div898/handbook/eda/section3/eda366g.htm
[guess]: http://git.tremily.us/?p=sawsim.git;a=blob;f=pysawsim/test/bell_rate.py;hb=837c425eaeccae280cc7f7784d03dfcfcb03678c#l106

[[!tag tags/sawsim]]
[[!tag tags/theory]]