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Author:
Sam Dreyfuss
Summary:
Causal effects on networks with double machine learning: ATE, direct and peer effects with confidence intervals that account for network dependence.
Latest version:
0.2.0
Required dependencies:
numpy
|
pandas
|
scikit-learn
|
scipy
Optional dependencies:
doubleml
|
joblib
|
mkdocs-material
|
mkdocstrings
|
neo4j
|
pytest
|
pytest-cov
|
ruff
|
statsmodels
|
tabulate
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