Require 'data' argument?
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question
- Dominant language
- R
- Stars
- 401
- Forks
- 136
- PR merge metrics
- No merged PRs in 30d
Description
I'm strongly in favor of this. Here are pros/cons:
Reason to require the data argument:
- Not requiring the
dataargument when specifying a model leads to all sorts of challenges for successfully implementing and maintaining the internals of rstanarm (or any other modeling package really).
Reasons not to require the data argument:
- Base R's
lm/glmand lme4'slmer/glmerset a very unfortunate precedent of not requiring this so we would be breaking with tradition if we were to require it. - @andrewgelman seems to like using the global environment but maybe we can convince him that the convenience is not worth the problems it introduces
Contributor guide
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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.
Research direction
Start by reading the discussion in issue #155, which weighs requiring the data argument against existing R modeling conventions. No files, tests, or implementation entry points are named; done would require an agreed behavior, implementation scope, and corresponding validation.
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