Comments (7)
amit-sharma
commented on June 4, 2024
Thanks @djinnome ! Definitely, implementing the ID algorithm is on our priority list, but being delayed with work on refutations. Would you be willing to contribute to the development?
Yes, I really the idea behind Whittemore--had a chance to talk to Joshua (who built Whittemore) a few weeks back.
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djinnome
commented on June 4, 2024
Hi Amit,
Implementing the ID algorithm, and possibly [the ID* and IDC* algorithms](https://arxiv.org/abs/1206.5294) in DoWhy would be exactly the kind of contribution our causality reading group is looking to make. We are about 1/3 of the way through
[Chapter 4](http://bayes.cs.ucla.edu/PRIMER/primer-ch4.pdf) of Judea Pearl's Causal Inference in Statistics: A Primer.
When we are done with that, we will focus our effort on the implementation of these algorithms.
Sincerely,
Jeremy
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amit-sharma
commented on June 4, 2024
Sounds great. Let me know once you are ready. Happy to chat in case you need you need more details on the library's code structure.
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gianlucadetommaso
commented on June 4, 2024
Hi all, was there meanwhile any progress on this front?
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amit-sharma
commented on June 4, 2024
yes, the ID algorithm is now implemented for identification.
https://microsoft.github.io/dowhy/example_notebooks/identifying_effects_using_id_algorithm.html
However, estimation based on the probability expressions returned by ID algorithm is not yet supported.
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gianlucadetommaso
commented on June 4, 2024
Thank you. Any chance somebody also implemented the Adjustment Criterion by Shpitser (here, Definition 5)? This is a complete criterion for identification via covariate adjustment.
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amit-sharma
commented on June 4, 2024
That's not implemented, but it will a simple exercise to implement it by extending the backdoor criterion. Would you like to implement it @gianlucadetommaso ? I've added an issue #402
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Related Issues (20)
- Backdoor path HOT 4
- Linear dataset functionality and parameters HOT 1
- Simple constraints for the SCM HOT 1
- How can I get more log messages from dowhy? HOT 4
- Identify effect not showing backdoor variable HOT 5
- numpy has no attribute 'long' HOT 1
- No common causes/confounders present. HOT 3
- Сausal effect for non-linear relationship HOT 1
- Compatability with networkx is broken HOT 8
- Continuous Treatment Variable HOT 1
- CausalEstimator reporting a 90% instead of 95% confidence interval for bootstrapping? HOT 5
- Hanging when refuting right after calculating confidence interval HOT 2
- Incomplete `method_name` argument documentation in `estimate_effect` HOT 4
- Add accessor to CausalModel._estimator_cache HOT 4
- Evaluation Metrics for Causal Graphs HOT 4
- Inconsistent encoding with pandas get_dummies causes prediction and effect estimation errors HOT 6
- Falsification of given DAG: not working on simulated data? HOT 4
- Causal Graph not provided. DoWhy will construct a graph based on data inputs. HOT 1
- how to use the function of estimate_effect of CausalModel class？ HOT 4
- gcm.arrow_strength providing different ranking HOT 6
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