Add inverse Gaussian distribution support
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- Dominant language
- C++
- Stars
- 839
- Forks
- 220
- Avg merge
- 2d 4h
- Merged PRs (30d)
- 14
Description
Description
Analogous to other distributions, add support for the inverse Gaussian distribution with a sampling statement and Stan functions for working with its log density, CDF, and CCDF.
This can be a wrapper around the Boost implementation of the distribution.
Example
The motivation is from writing a GLM with an inverse Gaussian. Similar to rstanarm, I implemented a custom helper function to perform the likelihood computation and it seems like other people in the past have re-implemented the same set of algorithms. For example, see here and here. It would be nice to have this as a library function.
Current Version:
v4.4.0
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
Start by reviewing the Boost inverse Gaussian distribution documentation and the analogous helper in rstanarm's src/stan_files/functions/continuous_likelihoods.stan. Compare the requested wrapper with existing distribution support, then verify that it provides a sampling statement and Stan functions for log density, CDF, and CCDF.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- cpp
- Domain
- backend
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 48/100