The iteration stops when (f^k-f^{k+1})/max{|f^k|,|f^{k+1}|,1}<=ftol.
gtol : float
The iteration will stop when max{|projg_i|i=1,...,n}<=gtol where pg_i is the i-th component of the projected gradient.
... but has not pgtol.
Thanks
- Stu
josef...@gmail.com
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Oct 6, 2017, 3:03:33 PM10/6/17
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to pystatsmodels
Our optimizers go through the original functions, our setup was written before `minimize` was added to scipy. I'm not sure how the options in `minimize` work (and whether they use callbacks to implement extra convergence criteria), but the relevant documentation for our wrapper are the fmin_xxx functions
This works also for the old optimizers like the default for minimize is to use bfgs. In that case, whatever options are available in scipy's minimize should be available through the **kwargs of fit.