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Notebook proposal
Title: Conditional vs interventional distributions
Why should this notebook be added to pymc-examples?
We only have a small number of notebooks covering causal inference topics so far. Causal inference is gaining more and more attention, so showcasing that PyMC can deal with Bayesian Causal inference is important. This particular notebook compares the conditional and interventional distributions and showcases the amazing new do operator. This is currently in pymc-experimental but will soon be moved into the main pymc repo.
This notebook will not compare and contrast interventions and counterfactuals. This will be left for another notebook.
Suggested categories:
- Level: beginner/intermediate
- Diataxis type: explanation
Related notebooks
None. But it will join the few existing notebooks in the Causal Inference subsection
References
- Causal Inference 2: Illustrating Interventions via a Toy Example by Ferenc Huszár.
- Almost certainly more, such as books by Pearl.
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proposalNew notebook proposal still up for discussionNew notebook proposal still up for discussion