Logit-normal or probit-normal as sampling distribution for `stat = "acc"`
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- Dominant language
- R
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- 114
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- 31
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Description
For stat = "acc", it would probably make sense to assume a normal distribution as the sampling distribution for a transformed estimator (transformed from the interval $(0, 1)$ to $(-\infty, \infty)$, similarly to stat = "mse" and stat = "rmse" where the estimators are transformed from $(0, \infty)$ to $(-\infty, \infty)$ in #496), see the discussion at https://github.com/stan-dev/projpred/pull/496#discussion_r1739354823.
Note that stat = "R2" is not concerned by this as it may get negative, see https://github.com/stan-dev/projpred/pull/496#discussion_r1919204537.
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.
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- Open a pull request that references the issue number.
Research direction
Start with the discussion linked from pull request #496 and review how the transformed sampling distributions for stat = "mse" and stat = "rmse" were handled. Decide whether acc should use a logit-normal or probit-normal distribution, then verify that R2 remains unaffected. Done means the chosen behavior is implemented and covered for stat = "acc".
Written by the indexing model from the issue text.
Assessment
- Tech stack
- r
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 38/100