[Feature Request] Statistical distributions roadmap
Nobody has claimed this yet.
Assessment
- Difficulty
- 5/5
- Estimated time
- Over a week
- Newbie friendliness
- 35/100
- Issue type
- Feature
- Clarity
- Needs clarification
- Activity status
- Quiet
- Tech stack
- fsharp
- Domain
- data
Research direction
Review the existing distribution implementations linked in src/FSharp.Stats/Distributions/Continuous and Discrete, then choose one unchecked item such as Cauchy, logistic, Lorentzian, or Weibull. The issue does not identify a specific entry point, tests, or acceptance criteria, so the completed work would need a defined distribution scope and validation expectations first.
Written by the indexing model from the issue text.
Description
Statistical distributions
- bernoulli
- beta
- binomial
- Cauchy
- chi
- chi-square
- exponential
- F-distribution
- gamma
- hypergeometric
- Kolmogorov-Smirnov #89
- logistic
- lognormal
- Lorentzian
- multivariate normal
- negative binomial (missing tests #256)
- normal
- Poisson
- Student's
- Weibull
- studentized range (missing fields)
- Dominant language
- F#
- Stars
- 228
- Forks
- 58
- Avg merge
- 2d 7h
- Merged PRs (30d)
- 1
Getting set up
- No Dockerfile or Docker Compose file
- Has a pull request template
- Read the contributing 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.
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