statsmodels / statsmodels/statsmodels
granger causality in the frequency domain
Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 11.6k
- Forks
- 3.6k
- Avg merge
- 7h 37m
- Merged PRs (30d)
- 96
Description
There is an implementation in nitime
based on Geweke
Breitung, Jörg, and Bertrand Candelon. 2006. “Testing for Short- and Long-run Causality: A Frequency-domain Approach.” Journal of Econometrics 132 (2) (June): 363–378. doi:10.1016/j.jeconom.2005.02.004.
thread at http://mail.scipy.org/pipermail/nipy-devel/2011-August/006640.html
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 reviewing the existing implementation in nitime, the Geweke and Breitung–Candelon references, and the linked nipy-devel thread. Determine the intended scope for adding frequency-domain Granger causality to statsmodels; completion should include a validated implementation aligned with the cited method.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- analytics
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100