tfcausalimpact
causal-learn
| tfcausalimpact | causal-learn | |
|---|---|---|
| 1 | 1 | |
| 579 | 992 | |
| - | 3.4% | |
| 4.0 | 7.9 | |
| 5 days ago | 26 days ago | |
| Python | Python | |
| Apache License 2.0 | MIT License |
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tfcausalimpact
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Slight issue with using this causal impact library
i found this library https://github.com/WillianFuks/tfcausalimpact which seems to be a python port of the R library
causal-learn
What are some alternatives?
dowhy - DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.
dodiscover - [Experimental] Global causal discovery algorithms
sections - Easy Python tree data structures
looper - A resource list for causality in statistics, data science and physics
HumesGuillotine - Hume's Guillotine: Beheading the social pseudo-sciences with the Algorithmic Information Criterion for CAUSAL model selection.
Structure_threader - A wrapper program to parallelize and automate runs of "Structure", "fastStructure" and "MavericK".
directory-structure - :package: Print a directory tree structure in your Python code.
genome_integration - MR-link and genome integration. genome_integration is a repository for the analysis of genomic data. Specifically, the repository implements the causal inference method MR-link, as well as other Mendelian randomization methods.