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Merge pull request #240 from lnccbrown/239-reorganize-documentation
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Documentation reorganization and various bug fixes
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digicosmos86 authored Jul 26, 2023
2 parents 01f0cd9 + 54da8c8 commit 0c54135
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2 changes: 1 addition & 1 deletion .gitignore
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site/

# folders in the repository
notebooks/
/notebooks
6 changes: 3 additions & 3 deletions README.md
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```

You will need optional dependencies to use JAX-based samplers and graph the models.
Please refer to our [installation guide](https://lnccbrown.github.io/HSSM/installation/)
Please refer to our [installation guide](https://lnccbrown.github.io/HSSM/getting_started/installation/)
for more detailed instructions.

**Note**: Possible solutions to any issues with installations with hssm can be located [here](https://github.com/lnccbrown/HSSM/discussions). We recommend leveraging an environment manager with Python 3.9~3.11 to prevent any problems with dependencies during the installation process. Please note that hssm is tested for python 3.9, 3.10, 3.11. Use other python versions with caution.
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model.sample()
```

To quickly get started with HSSM, please follow [this tutorial](https://lnccbrown.github.io/HSSM/tutorial_notebooks/no_execute/getting_started/).
For a deeper dive into HSSM, please follow [our main tutorial](https://lnccbrown.github.io/HSSM/tutorial_notebooks/no_execute/main_tutorial/).
To quickly get started with HSSM, please follow [this tutorial](https://lnccbrown.github.io/HSSM/getting_started/getting_started/).
For a deeper dive into HSSM, please follow [our main tutorial](https://lnccbrown.github.io/HSSM/tutorials/main_tutorial/).

## License

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9 changes: 9 additions & 0 deletions docs/changelog.md
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## 0.1.x

### 0.1.3

- Added the ability to specify `inf`s in bounds.
- Fixed an issue where `nuts_numpyro` sampler fails with regression and lapse distribution.
- Defaults to `nuts_numpyro` sampler with `approx_differentiable` likelihoods and `jax` backend.
- Added a `hssm.show_defaults()` convenience function to print out default configs.
- Added default `blackbox` likelihoods for `ddm` and `ddm_sdv` models.
- Various under-the-hood documentation improvements.

### 0.1.2

- Improved numerical stability of `analytical` likelihoods.
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