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Implement more robust jitter init (resolves #4107) #4298

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Update Release notes
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ricardoV94 committed Dec 5, 2020
commit 12769fae8493a031c70b5bbcdf4374f58fed7853
1 change: 1 addition & 0 deletions RELEASE-NOTES.md
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Expand Up @@ -48,6 +48,7 @@ This new version of `Theano-PyMC` comes with an experimental JAX backend which,
- Fix bug in `model.check_test_point` that caused the `test_point` argument to be ignored. (see [PR #4211](https://github.com/pymc-devs/pymc3/pull/4211#issuecomment-727142721))
- Refactored MvNormal.random method with better handling of sample, batch and event shapes. [#4207](https://github.com/pymc-devs/pymc3/pull/4207)
- The `InverseGamma` distribution now implements a `logcdf`. [#3944](https://github.com/pymc-devs/pymc3/pull/3944)
- Make starting jitter methods for nuts sampling more robust by resampling values that lead to non-finite probabilities. A new optional argument `jitter-max-retries` can be passed to `pm.sample()` and `pm.init_nuts()` to control the maximum number of retries per chain. [4298](https://github.com/pymc-devs/pymc3/pull/4298)

### Documentation
- Added a new notebook demonstrating how to incorporate sampling from a conjugate Dirichlet-multinomial posterior density in conjunction with other step methods (see [#4199](https://github.com/pymc-devs/pymc3/pull/4199)).
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