ENH: MNLogit identification with categorical variables
Nobody has claimed this yet.
Assessment
- Difficulty
- 5/5
- Estimated time
- Over a week
- Newbie friendliness
- 25/100
Research direction
Start with the linked Stack Overflow report and establish the identification condition for MNLogit with categorical variables. Then determine whether the proposed hessian_pinv option addresses the issue and what behavior should be tested; the payload names no repository files, entry points, or tests.
Written by the indexing model from the issue text.
Description
https://stackoverflow.com/questions/77352027/mnlogit-summary-return-a-array-with-a-lot-of-nan
My guess would be that if we have categorical variables, then we need observations for each endog/exog-cat cell.
But I'm not sure what identification condition we need.
possible workaround:
add option hessian_pinv=True to use pinv for hessian that is only semi-definite but not positive definite.
- Dominant language
- Python
- Stars
- 11.6k
- Forks
- 3.6k
- Avg merge
- 7h 37m
- Merged PRs (30d)
- 96
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.
More from statsmodels/statsmodels
-
Difficulty 1/5 Under an hour Newbie friendliness 90/100
statsmodels/statsmodels#10271 ·
-
type-bug
Difficulty 2/5 1-3 hours Newbie friendliness 78/100
statsmodels/statsmodels#10269 ·
-
Documentation
Difficulty 2/5 1-3 hours Newbie friendliness 92/100
statsmodels/statsmodels#10266 ·
-
Difficulty 1/5 Under an hour Newbie friendliness 78/100
statsmodels/statsmodels#9627 · 1 comment ·
-
Difficulty 2/5 1-3 hours Newbie friendliness 62/100
statsmodels/statsmodels#9293 · 1 comment ·
All issues in statsmodels/statsmodels
Similar issues
-
Difficulty 2/5 1-3 hours Newbie friendliness 74/100
bancolombia/sentinel#23 ·
-
test md OpenCI
Difficulty 2/5 1-3 hours Newbie friendliness 74/100
-
integration:quickjs org:external priority:backlog topic:code-interpreter topic:middleware type:feature
Difficulty 2/5 1-3 hours Newbie friendliness 74/100
langchain-ai/deepagents#6450 ·
-
bug client
Difficulty 2/5 1-3 hours Newbie friendliness 88/100
-
Difficulty 2/5 1-3 hours Newbie friendliness 74/100