tensorflow / tensorflow/probability
Inclusion of SARIMAX model
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Description
SARIMAX is another model with a lot of potential in the time-series forecasting space due to its ability to factor in extra covariants as well as factor in seasonality into the traditional ARIMA model. I'm not sure what the changes would need to be since ARIMA is already implemented, but it seems like an improvement to existing models.
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 identified in the issue. Start by locating the existing ARIMA implementation and determining how SARIMAX support would fit its API, including covariates and seasonality. Done means the project has a defined, tested SARIMAX model with agreed behavior.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- tensorflow
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 30/100