Estimagic-Least-Squares-Example

This repository contains a Jupyter Notebook that complements a Pull Request to estimagic.

The PR adds two algorithms from the scipy.optimize.least_squares optimizer, namely scipy_ls_trf and scipy_ls_dogbox.

The Notebook is used as a supplementary material for assessment for the course OSE: Scientific Computing, Winter Semester 2020/21, Univesity of Bonn by Prof. Philipp Eisenhauer within the Open Source Economics Innitiative.

Usage

In order to use this Notebook, you need to install the estimagic fork.

The fork is added as a submodule to this repository.

To install the estimagic fork, run:

# Clone recursive to also fetch the submodule
git clone --recursive https://github.com/yradeva93/Estimagic-Least-Squares-Example
# Change into fork's subdirectory
cd Estimagic-Least-Squares-Example/estimagic
# Install environment
conda env create -f environment.yml
conda activate estimagic
pip install -e .
# Go to Notebook directory
cd ..
# Run jupyter
jupyter notebook

Your default web browser with the loaded Notebook should open now.