pymc-devs / pymc-devs/pymc-examples
Conditional Autoregressive (CAR) Models for Spatial Data
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- Dominant language
- Python
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Description
Notebook proposal
Title: Conditional Autoregressive (CAR) Models for Spatial Data
Why should this notebook be added to pymc-examples?
The CAR distribution is within the multivariate distributions that PyMC supports, but there are no notebooks that offer an example.
Suggested categories:
- Level: beginner
- Diataxis type: tutorial
Related notebooks
Junpeng wrote this great notebook on CAR priors, but this was pre the CAR distribution being a part of PyMC and for version 3.
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 reading the related pre-PyMC-v4 CAR-prior notebook linked in the issue and compare it with the current CAR distribution. Create a beginner-level tutorial notebook for CAR models on spatial data, using the existing notebook as a reference. Done means the example demonstrates the current distribution and is suitable for the suggested tutorial category.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- jupyter-notebook, python
- Domain
- data, documentation
- Issue type
- Documentation
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 45/100