cdt15/lingam
Python package for causal discovery based on LiNGAM.
This package helps you uncover cause-and-effect relationships from observational data, even when traditional correlation methods fall short. By analyzing your numerical datasets, it reveals the underlying causal order and direct influences between variables. It's designed for researchers, data scientists, and analysts who need to understand 'why' something is happening, not just 'what' is correlated.
474 stars. Used by 1 other package. Available on PyPI.
Use this if you need to determine the causal structure between variables in your dataset, especially when the data isn't perfectly 'bell-shaped' or Gaussian.
Not ideal if your primary goal is simple prediction or correlation analysis without needing to infer direct cause-and-effect pathways.
Stars
474
Forks
71
Language
Python
License
MIT
Category
Last pushed
Mar 02, 2026
Commits (30d)
0
Dependencies
12
Reverse dependents
1
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