Ananke: A module for causal inference¶
How to install¶
Install graphviz using the appropriate method for your OS
# Ubuntu
sudo apt install graphviz libgraphviz-dev pkg-config
# Mac
brew install graphviz
# Mac (M1)
## see https://github.com/pygraphviz/pygraphviz/issues/398
brew install graphviz
python -m pip install \
--global-option=build_ext \
--global-option="-I$(brew --prefix graphviz)/include/" \
--global-option="-L$(brew --prefix graphviz)/lib/" \
pygraphviz
# Fedora
sudo yum install graphviz
Install the latest release using pip.
pip3 install ananke-causal
For more details please see the gitlab, or the documentation for details on how to use Ananke.
Documentation¶
Contents:
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notebooks/code-snippets.ipynb
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Citation¶
If you enjoyed this package, we would appreciate the following citations:
- BNS20
Rohit Bhattacharya, Razieh Nabi, and Ilya Shpitser. Semiparametric inference for causal effects in graphical models with hidden variables. arXiv preprint arXiv:2003.12659, 2020.
- LS20
Jaron J. R. Lee and Ilya Shpitser. Identification Methods With Arbitrary Interventional Distributions as Inputs. arXiv preprint arXiv:2004.01157 [cs, stat], 2020.
- NBS20
Razieh Nabi, Rohit Bhattacharya, and Ilya Shpitser. Full law identification in graphical models of missing data: completeness results. arXiv preprint arXiv:2004.04872, 2020.
Contributors¶
Rohit Bhattacharya
Jaron Lee
Razieh Nabi
Preethi Prakash
Ranjani Srinivasan