PEtab-dev / PEtab-dev/petab_select
Check for plausible likelihoods in case of nested models
Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 14
- Forks
- 1
- PR merge metrics
- No merged PRs in 30d
Description
Maybe I missed it, but I don't think it's implemented yet:
It would be nice (to have an option) to automatically check whether in case of nested models and identical datasets, the super-model has a likelihood at least as good as any submodel. If this is not the case, this is most likely due to non-converged optimizations, and should be communicated to the user.
Contributor guide
No contributing guide indexed for this repository
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 or tests are named. Start by locating the entry points for nested-model comparison and likelihood evaluation, then determine how an optional plausibility check should identify identical datasets and report a submodel with a better likelihood. Done means the option is documented and the non-convergence warning is covered by tests.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- data
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100