Naming scheme for `fit_` functions
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Assessment
- Difficulty
- 5/5
- Estimated time
- Over a week
- Newbie friendliness
- 25/100
- Issue type
- Refactor
- Clarity
- Needs clarification
- Activity status
- Stale
- Tech stack
- r
- Domain
- developer-experience
Research direction
Start by reviewing the existing fit_nbbp_[descriptor]_[method] function names and the package scope described in the issue. Resolve whether the descriptor and _nbbp prefix are needed, agree on terminology for the shared R and k parameters, and define the final naming scheme.
Written by the indexing model from the issue text.
Description
Currently, we name functions fit_nbbp_[descriptor]_[method] where
[method]is either Bayesian inference or maximum likelihood inference[descriptor]is only "homogenous"
To consider:
- Is
[descriptor]speculative generality for unimplemented options, or useful space for a future where there are spatiotemporal or hierarchical models? - Is
homogenousa good description anyways? What we really mean is that all the chain sizes will be considered to have the same $R$ and $k$ parameters. We're already beyond IID, since we allow different censoring schemes for different chains. - The
_nbbppart is probably also redundant, since the package scope is in the package name: NBBP models.
Shoutout to @swo for pointing this out.
- Dominant language
- R
- Stars
- 2
- Forks
- 3
- PR merge metrics
- No merged PRs in 30d
Getting set up
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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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