Why should this notebook be added to pymc-examples?
There is a lot of excitement about causal inference at the moment. Interventions and Counterfactuals map on to Pearl's Rung 2 and Rung 3 of the causal ladder. So having a notebook that succinctly explains the concepts and how to implement these in PyMC would be valuable.
I'd aim to introduce the concepts, then illustrate with a practical example. This could perhaps be time-series based in order to emphasise the retrospective vs prospective aspects of intervention and counterfactuals.
Notebook proposal
Title: Interventions versus counterfactuals
Why should this notebook be added to pymc-examples?
There is a lot of excitement about causal inference at the moment. Interventions and Counterfactuals map on to Pearl's Rung 2 and Rung 3 of the causal ladder. So having a notebook that succinctly explains the concepts and how to implement these in PyMC would be valuable.
I'd aim to introduce the concepts, then illustrate with a practical example. This could perhaps be time-series based in order to emphasise the retrospective vs prospective aspects of intervention and counterfactuals.
Suggested categories:
Related notebooks
This notebook would compliment the range of other causal focussed notebooks that I've put together:
It could be a good sequel to the Interventional distributions and graph mutation with the do-operator example, but it wouldn't really overlap with it.
References