Consistent standard errors for longitudinal data collected under pooling online decision policies.
Project description
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Save your standard errors from pooling in online decision-making algorithms.
Setup (if not using conda)
Create and activate a virtual environment
python3 -m venv .venv; source /.venv/bin/activate
Adding a package
- Add to
requirements.txtwith a specific version or no version if you want the latest stable - Run
pip freeze > requirements.txtto lock the versions of your package and all its subpackages
Running the code
- `export PYTHONPATH to the absolute path of this repository on your computer
./run_local_synthetic.sh, which outputs tosimulated_data/by default. See all the possible flags to be toggled in the script code.
Linting/Formatting
Testing
python -m pytest python -m pytest tests/unit_tests python -m pytest tests/integration_tests
TODO
- Add precommit hooks (pip freeze, linting, formatting)
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