lingam 0.9.0

LiNGAM Python Package

LiNGAM - Discovery of non-gaussian linear causal models

LiNGAM is a new method for estimating structural equation models or linear Bayesian networks. It is based on using the non-Gaussianity of the data.

• The LiNGAM Project.

Requirements

• Python3
• numpy
• scipy
• scikit-learn

Installation

To install lingam package, use pip as follows:

$ pip install lingam

Documentation

Tutrial and API reference

License

This project is licensed under the terms of the MIT license.

Reference Papers

• S. Shimizu, P. O. Hoyer, A. Hyvﾃ､rinen and A. Kerminen. A linear non-gaussian acyclic model for causal discovery. Journal of Machine Learning Research, 7: 2003--2030, 2006. [PDF]
• S. Shimizu, T. Inazumi, Y. Sogawa, A. Hyvﾃ､rinen, Y. Kawahara, T. Washio, P. O. Hoyer and K. Bollen. DirectLiNGAM: A direct method for learning a linear non-Gaussian structural equation model. Journal of Machine Learning Research, 12(Apr): 1225--1248, 2011. [PDF]
• A. Hyvﾃ､rinen and S. M. Smith. Pairwise likelihood ratios for estimation of non-Gaussian structural equation models. Journal of Machine Learning Research, 14(Jan): 111--152, 2013. [PDF]