naturally parameterized multivariate normal
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- Dominant language
- C++
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Description
From Andrew:
Add a paraemterization of the multivariate normal that takes the parameters Sigma^{-1}*mu and Sigma^{-1} (i.e., the so-called natural parameters of the exponential family) rather than mu and Sigma?
I'm asking because, in this MC-EP thing I'm playing around with, I find myself doing a lot of inverting matrices and solving linear systems in order to get mu and Sigma to pass in to my prior distribution. It's no big deal in terms of "wall time" (the dimensionality is low), I was just wondering.
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
Locate the multivariate normal distribution implementation and its existing parameterization API. Read how mu and Sigma are represented and tested, then define completion as supporting Sigma^{-1}*mu and Sigma^{-1} directly without requiring the conversions described in the issue, with corresponding tests for the new interface.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- cpp
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 30/100