statsmodels / statsmodels/statsmodels
SUMM: diagnostic tests, measures and plots
Nobody has claimed this yet.
- Dominant language
- Python
- Stars
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- Forks
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- Avg merge
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- Merged PRs (30d)
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Description
(this is another topic that is missing consistent implementation across models.)
(I might add a topic_diagnostic label, but don't want to go through issues right now. Search shows many open isssues.)
This is mainly about checking underlying assumption and specification tests.
Postestimation in general is more about interpretation of model.
main tasks, design
- implementation of functions and methods across models (or check generalization and applicability)
- easy access for users (e.g.
get_diagnostics,get_plots,check_sanity) - documentation (suggest possible remedies? maybe not that)
main issues by models
- linear regression: ok
- tsa: PR by Chad for some models
- GLM/discrete: essentially nothing
issues by topic
...
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
No files, tests, or entry points are named. Start by reviewing the listed model and topic breakdown, including the existing linear-regression work and the referenced time-series pull request, then define the scope and applicability of diagnostics across models. Done requires an agreed design for implementation, user access, and documentation.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- data, testing-qa
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100