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 perform statistical inference on estimated parameters.
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 perform statistical inference on estimated parameters.
The package can be installed via conda. To do so, type the following commands in a terminal:
$ conda config --add channels conda-forge
$ conda install estimagic
The first line adds conda-forge to your conda channels. This is necessary for conda to find all dependencies of estimagic. The second line installs estimagic and its dependencies.
Only scipy
is a mandatory dependency of estimagic. Other algorithms become available
if you install more packages. We make this optional because most of the time you will
use at least one additional package, but only very rarely will you need all of them.
For an overview of all optimizers and the packages you need to install to enable them
see {ref}list_of_algorithms
.
To enable all algorithms at once, do the following:
conda install nlopt
pip install Py-BOBYQA
pip install DFO-LS
conda install petsc4py
(Not available on Windows)
conda install cyipopt
conda install pygmo
pip install fides>=0.7.4 (Make sure you have at least 0.7.1)
The documentation is hosted (on rtd)
If you use Estimagic for your research, please do not forget to cite it.
@Unpublished{Gabler2022,
Title = {A Python Tool for the Estimation of large scale scientific models.},
Author = {Janos Gabler},
Year = {2022},
Url = {https://github.com/OpenSourceEconomics/estimagic}
}