estimagic
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Estimagic is a Python package for nonlinear optimization with or without constraints. It is particularly suited to solve difficult nonlinear estimation problems. On top, it provides functionality to p...
updates: - [github.com/asottile/pyupgrade: v3.2.3 → v3.3.0](https://github.com/asottile/pyupgrade/compare/v3.2.3...v3.3.0) - [github.com/PyCQA/flake8: 5.0.4 → 6.0.0](https://github.com/PyCQA/flake8/compare/5.0.4...6.0.0) - [github.com/mgedmin/check-manifest: 0.48 → 0.49](https://github.com/mgedmin/check-manifest/compare/0.48...0.49)
Add function to calculate the lambda poisedness of a sample.
- Allow to easily add a row of strings like `"Controls": ["Yes", "No"])` to the footer before calling `render_latex`. - Do not round all cells which contain integer values Closes...
Nonlinear constraints are not well documented. - [ ] Improve relevant docstrings - [ ] Extend example in notebooks
### Bug description Running `estimate_ml`with fides returns failure with message: ``` Maximize with 95 free parameters terminated unsuccessfully after 2802 iterations. The value of criterion improved from -1184865.5053305852 to -1029883.7752618275....
Related to #405: While that particular issue is somewhat fides-specific, the broader point relates to interpreting the convergence report produced by estimagic: ``` Maximize with 95 free parameters terminated unsuccessfully...
Add bounds to BHHH algorithm. To-Do: - [x] Implement box constraints - [x] Refactor - [x] Add more test cases
This enhancement was suggested by [Johannes Schmieder](https://sites.google.com/site/johannesschmieder/?pli=1) ### Current Situation The default sampling method in multistart optimization is a non-randomized sobol sampling. This is unexpected for users and a problem...