truncated PRNGs
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- Dominant language
- C++
- Stars
- 839
- Forks
- 220
- Avg merge
- 2d 4h
- Merged PRs (30d)
- 14
Description
It'd be nice to be able to match our models and do something like this:
sigma_sim <- normal_rng(mu, sigma) T[lb, ];
to get a truncated form of the normal (and so on for upper and lower bounds and just upper bounds).
What we need in this repo is truncated forms of the PRNGs. Rejection sampling won't be robust enough and writing a slice sampler seems like a huge pain and I'm not even clear it'll work for fat tails like the Cauchy or constrained distributions without transformed. Will this have to wait until we have inverse CDFs?
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
No files, tests, or entry points are named. Start by locating the existing PRNG implementations and their tests, then determine how truncated normal and other distributions would be represented; done would require a decided, robust approach for the requested bounds and distributions.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- cpp
- Domain
- backend
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100