| Name | bayesian-models JSON |
| Version |
0.1.0
JSON |
| download |
| home_page | |
| Summary | A package for building common bayesian models in pymc |
| upload_time | 2023-04-05 09:14:06 |
| maintainer | |
| docs_url | None |
| author | |
| requires_python | |
| license | |
| keywords |
bayesian
models
statistics
pymc
|
| VCS |
|
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
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No Travis.
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| coveralls test coverage |
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|
# bayesian-models
`bayeian-models` is a small library build on top of `pymc` that
implements common statistical models
`bayesian_models` aims to implement `sklearn` style classes,
representing general types of models a user may wish to specify. Since
there is a very large variety of statistical models available, only some
are included in this library in a somewhat ad-hoc manner. The following
models are planned for implementation:
* BEST (Bayesian Estimation Superceeds the t Test) := Statistical
comparisons' between groups, analoguous to hypothesis testing
(COMPLETED)
## Installation
`bayesian-models` can be installed with pip
```
pip install bayesian-models
```
Newer releases are first published to TestPyPI. They are installable as
follows
```
pip install --index-url https://test.pypi.org/simple/ --extra-index-url https://pypi.org/simple bayesian-models
```
To install from git:
```
pip install git+ssh://git@github.com/AlexRodis/bayesian-models.git
```
To install the developement version run:
```
pip install 'bayesian_models[dev]@ git+ssh://git@github.com/AlexRodis/bayesian_models.git@dev-main'
```
It is often desirable to run models with a GPU if available. At present,
there are known issues with the `numpyro` dependency. Only these
versions are supported:
```
jax==0.4.1
jaxlib==0.4.1
```
To attempt to install with GPU support run:
```
pip install 'bayesian_models[GPU]@git+ssh://git@github.com/AlexRodis/bayesian-models.git'
```
Note: the GPU version is unstable
You must also set the following environment variable prior to all other
commands, including imports
```
XLA_PYTHON_CLIENT_PREALLOCATE=false
```
These dependencies are only required with
`pymc.sampling.jax.sample_numpyro_nuts` and if using the default options
can be ignored
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"description": "# bayesian-models\n`bayeian-models` is a small library build on top of `pymc` that\nimplements common statistical models\n\n`bayesian_models` aims to implement `sklearn` style classes,\nrepresenting general types of models a user may wish to specify. Since\nthere is a very large variety of statistical models available, only some\nare included in this library in a somewhat ad-hoc manner. The following\nmodels are planned for implementation:\n\n* BEST (Bayesian Estimation Superceeds the t Test) := Statistical\n comparisons' between groups, analoguous to hypothesis testing\n (COMPLETED)\n\n## Installation\n\n`bayesian-models` can be installed with pip\n\n```\npip install bayesian-models\n```\n\nNewer releases are first published to TestPyPI. They are installable as\nfollows\n\n```\npip install --index-url https://test.pypi.org/simple/ --extra-index-url https://pypi.org/simple bayesian-models\n```\n\nTo install from git:\n\n```\npip install git+ssh://git@github.com/AlexRodis/bayesian-models.git\n```\n\nTo install the developement version run:\n```\npip install 'bayesian_models[dev]@ git+ssh://git@github.com/AlexRodis/bayesian_models.git@dev-main'\n```\n\nIt is often desirable to run models with a GPU if available. At present,\nthere are known issues with the `numpyro` dependency. Only these\nversions are supported:\n\n```\njax==0.4.1\njaxlib==0.4.1\n```\n\n\nTo attempt to install with GPU support run:\n\n```\npip install 'bayesian_models[GPU]@git+ssh://git@github.com/AlexRodis/bayesian-models.git'\n```\n\nNote: the GPU version is unstable\n\nYou must also set the following environment variable prior to all other\ncommands, including imports\n\n```\nXLA_PYTHON_CLIENT_PREALLOCATE=false\n```\n\nThese dependencies are only required with\n`pymc.sampling.jax.sample_numpyro_nuts` and if using the default options\ncan be ignored\n\n",
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