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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.txt with a specific version or no version if you want the latest stable
  • Run pip freeze > requirements.txt to 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 to simulated_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

  1. Add precommit hooks (pip freeze, linting, formatting)

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