pymc
https://github.com/pymc-devs/pymc
Python
Bayesian Modeling in Python
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- Issues
- Refactor `init` logic in `pm.sample`
- Add InverseWishart distribution
- Add way to set backend `fn` random generators
- BUG: `KeyError: 'diverging'` when setting up `CategoricalGibbsMetropolis` step method with `proposal=‘proportional’`
- Add `record_sampling_state` to `NDArray` backend
- Implement Ordered distribution factory
- BUG: input a ndarray type data but still raise an error: setting an array element with a sequence.
- BUG: blackjax sampler gives Incorrect output dtype for return value #0: Expected: int64, Actual: int32
- trace fn does not respect random seed for stochastic "Deterministics"
- Compute only dependent logp in step samplers
- Docs
- Python not yet supported