estimate_dispersion() (and maybe estimate_zeroinflation()?)
Nobody has claimed this yet.
Assessment
- Difficulty
- 5/5
- Estimated time
- Over a week
- Newbie friendliness
- 25/100
Research direction
Start by reading estimate_prediction() and estimate_response(), then review the linked insight issue about dispersion support. Define the intended scope for modeled-dispersion prediction intervals, predicted dispersion with confidence intervals, and zero-inflation predictions before locating the relevant implementation and tests. Done means the supported options and output scales are documented and covered by tests.
Written by the indexing model from the issue text.
Description
For models with dispersion models, it would be nice if two things were possible:
- Incorporation of modeled dispersion parameters into prediction intervals in
estimate_prediction(). - Estimate predicted dispersion and confidence intervals on the link or response scale. This could be an option in
estimate_response()and related functions (cf. https://github.com/easystats/insight/issues/413) or a separateestimate_dispersion(). Like withestimate_prediction(), making this an alias ofestimate_response()with default options might make sense.
Relatedly, options for estimating zero-inflation predictions would be great.
- Dominant language
- R
- Stars
- 263
- Forks
- 22
- Avg merge
- 1h 22m
- Merged PRs (30d)
- 11
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.
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