pymc-devs/pymc

Implement more Dims distributions

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#7,874 opened on Jul 25, 2025

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dimshackathonhelp wanted

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Description

Description

We have these currently:

We should implement most of the existing distributions. Univariate should be straightforward.

Multivariate may be trickier. We would likely want to reuse the regular methods like we do for ZeroSumNormal and MvNormal, but we need to test carefully.

Distribution factories like Mixture, Truncated, Censored will be the trickiest. The first step is to implement an extend_dist_dims function (to recreate the input distributions with more dims, just like we used to having to change_dist_size before).

Contributor guide

Research direction
Study the existing Scalar and Vector distributions in the dims/distributions module. Implement the `extend dist dims` function to recreate input distributions with more dims. Start with univariate distributions, then tackle multivariate following the pattern in ZeroSumNormal and MvNormal. Finally, handle distribution factories like Mixture, Truncated, and Censored.
Tech stack
python
Domain
machine learning
Issue type
Feature
DifficultyEstimated implementation difficulty for a new contributor, from 1 for very small changes to 5 for expert-level work.
3
Estimated timeA rough time range for an experienced contributor to investigate, implement, test, and prepare a pull request.
3-5 days
Activity statusHow available the issue appears right now: fresh, active, stale, blocked, or waiting on maintainer input.
Active
ClarityHow clearly the issue explains the expected change, acceptance criteria, and next step.
Clear
Prerequisites
PythonGit
Newbie friendlinessA 1-100 score estimating how approachable this issue is for first-time contributors.
50