Handle frequency weights with loo
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- Dominant language
- R
- Stars
- 157
- Forks
- 38
- Avg merge
- 4d 16h
- Merged PRs (30d)
- 2
Description
In some cases models are specified ("compressed") with frequency weights to speed up the fitting, however, this doesn't work well with loo as the Pareto k's indicates that all observations are heavily influencing the posterior, which of course it true on the aggregated level, but may not be true in the disaggregated level. Some kind of adjustment (I suppose disaggregation of the log-likelihood is a part of it) would be needed for such a case.
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 named. Start by reviewing how loo handles frequency-weighted or compressed models and how log-likelihood observations are represented. Define the required adjustment for disaggregated observations and validate that Pareto k diagnostics reflect the intended observation level.
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Assessment
- Tech stack
- r
- Domain
- data
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100