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.




Estimation and Inference#

  • You can estimate a model using method of simulated moments (MSM), calculate standard errors and do sensitivity analysis with just one function call. See MSM Tutorial

  • Asymptotic standard errors for maximum likelihood estimation.

  • estimagic also provides bootstrap confidence intervals and standard errors. Of course the bootstrap procedures are parallelized.

Numerical differentiation#

  • estimagic can calculate precise numerical derivatives using Richardson extrapolations.

  • Function evaluations needed for numerical derivatives can be done in parallel with pre-implemented or user provided batch evaluators.

Useful links for search: Index | Module Index | Search Page