Implement survival models
Nobody has claimed this yet.
- Dominant language
- R
- Stars
- 114
- Forks
- 31
- PR merge metrics
- No merged PRs in 30d
Description
We need to implement the projection for survival models at some point. The actual implementation needs some thinking and is likely to depend on how the survival models are/will be handled in rstanarm (issue https://github.com/stan-dev/rstanarm/issues/69) and in package survival. But this is mainly related to how this appears to the user. Regarding the projection itself, there should not be too many difficulties provided the likelihood is log-concave.
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 linked rstanarm issue 69 and reviewing how survival models are handled in the survival package. Then trace the project's existing projection entry points and determine the user-facing behavior needed for survival models, including whether the log-concave likelihood assumption applies; done means the expected scope and integration path are documented.
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
- 25/100