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

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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

Ananke Graphs

ananke.graphs package

Ananke Identification

ananke.identification package

Ananke Estimation

ananke.estimation package

Ananke Models

ananke.models package

Indices and Tables