Smoothed Bayesian Bootstrap
Open
Nobody has claimed this yet.
feature
- Dominant language
- R
- Stars
- 157
- Forks
- 38
- Avg merge
- 4d 16h
- Merged PRs (30d)
- 2
Description
As described here; drawing from a Bayesian bootstrap, smoothed with a uniform interpolation between points, gives some pretty big improvements to the quality of inferences.
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 reading the two linked papers to understand the proposed smoothed Bayesian bootstrap and how it relates to loo's existing inference methods. Then inspect the repository's current bootstrap and model-comparison entry points, if any. Done means the method is integrated and its inference-quality improvements are supported by appropriate comparisons.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- r
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100