Sparse matrix in R incompatible with STAN
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Description
Summary:
Integrate R's sparse matrix class from the Matrix library with STAN.
Description:
When I use the Sparse Matrix class in R, provided by the Matrix package, my data-set is ~ 10 Mb. But when I call an RStan program I need to convert my matrix using as.matrix() base class in order for the function to work.
Unfortunately, my matrix is very sparse so my data-set goes from 10 Mb to 2 GB when I call as.matrix, and my R session crashes due to memory error.
My question is: can STAN use the SparseMatrix class from R in its computation? If so, how would I go about using this?
Reproducible Steps:
Current Output:
If applicable, any relevant output from RStan.
Expected Output:
If applicable, the output you expected from RStan.
RStan Version:
2.21.1
R Version:
4.02
Operating System:
Your operating system (e.g., Ubuntu 20.04
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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 with R's Matrix sparse-matrix class and the as.matrix() conversion described in the report; confirm how an RStan program currently receives matrix data. Done means the requested sparse input path is either supported without densifying the dataset or its limitation and usage are clearly documented.
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Assessment
- Tech stack
- r
- Domain
- data
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100