Adds Wishart and InverseWishart distributions
#170
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…and its log variant `mvlgamma`
…hart distribution implementation
…hart distribution implementation
… pseudo inverse doesn't do this due to approximation
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Thanks for contributing, I do want to introduce this, but after release 0.17 since we're hoping to get more feedback on the multivariate API, see #209, and this should match what have there. |
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Thanks! Sounds good. I am keeping an eye on it. Let me know if any changes need to be made. |
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#209 is merged, Modifications to match are mostly in the pattern of choosing |
YeungOnion
reviewed
Aug 7, 2024
| let s = w.sample(rng); | ||
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| s.cholesky().unwrap().inverse().symmetric_part() | ||
| } |
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Would you consider implementing sample_iter to rely on a single conversion to Wishart to obtain multiple samples?
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This pr adds
WishartandInverseWishartdistributions along with multivariate gamma functionsmvgammaandmvlgamma.mathnet implementations were used as a reference: Wishart and Inverse Wishart
The Distributions.jl Julia package was used to create the testcases and as a cross-reference.
Thanks
Edit: Sorry for creating a duplicate pr. I have closed the previous one.