statsmodels / statsmodels/statsmodels
ENH: confidence interval for Logit, seaborn
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Description
I haven't looked at the details. This is mainly a reference to a (down stream) use case.
seaborn has bootstrap confidence intervals for logistic regression, which is slow. We should have them available without bootstrap (via endpoint transformation of linear prediction confidence intervals)
https://github.com/mwaskom/seaborn/issues/347#issuecomment-60974777
http://tomwallis.info/2014/10/29/high-level-plotting-in-python/
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by reading the Logit implementation and its existing confidence-interval or prediction APIs. Review the linked seaborn discussion and the endpoint-transformation reference to determine the expected behavior. Done means Logit exposes non-bootstrap confidence intervals suitable for the downstream seaborn use case, with project tests covering the result.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- data
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100