How to calculate confidence intervals for average impact over a subset of data?
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Description
Most EconML models offer a way to generate a confidence interval for the point estimates of causal impact.
What I need is to calculate confidence intervals over subsets of points, eg split by the estimated impact.
Example: I want to estimate the confidence interval for the impact averaged over the data points where the model predicts positive impact.
Can you suggest any way to do so, at least for some models, that is less compute-intensive than just bootstrapping?
Thanks a lot!
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Research direction
No file, test, or entry point is named. Start by reviewing the relevant EconML estimators' confidence-interval APIs and inference documentation; done would be a validated, less compute-intensive method for confidence intervals over subset-averaged effects, or a clearly documented limitation.
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Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100