Metadata-Version: 2.4
Name: arviz-stats
Version: 1.1.0
Summary: Statistical computation and diagnostics for ArviZ.
Author-email: ArviZ team <arvizdevs@gmail.com>
Requires-Python: >=3.12
Description-Content-Type: text/markdown
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Education
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Programming Language :: Python :: 3.14
License-File: LICENSE
Requires-Dist: numpy>=2
Requires-Dist: scipy>=1.13
Requires-Dist: sphinx-book-theme ; extra == "doc"
Requires-Dist: myst-parser[linkify] ; extra == "doc"
Requires-Dist: myst-nb ; extra == "doc"
Requires-Dist: sphinx-copybutton ; extra == "doc"
Requires-Dist: numpydoc ; extra == "doc"
Requires-Dist: sphinx<9 ; extra == "doc"
Requires-Dist: sphinx-design ; extra == "doc"
Requires-Dist: jupyter-sphinx ; extra == "doc"
Requires-Dist: h5netcdf[h5py] ; extra == "doc"
Requires-Dist: sphinx_autosummary_accessors ; extra == "doc"
Requires-Dist: numba ; extra == "numba"
Requires-Dist: xarray_einstats[einops, numba] ; extra == "numba"
Requires-Dist: pytest ; extra == "test"
Requires-Dist: pytest-cov ; extra == "test"
Requires-Dist: pytest ; extra == "test-xarray"
Requires-Dist: pytest-cov ; extra == "test-xarray"
Requires-Dist: h5netcdf[h5py] ; extra == "test-xarray"
Requires-Dist: arviz-base>=1.1,<1.2 ; extra == "xarray"
Requires-Dist: xarray-einstats ; extra == "xarray"
Requires-Dist: xarray>=2024.11.0 ; extra == "xarray"
Project-URL: documentation, https://arviz-stats.readthedocs.io
Project-URL: funding, https://opencollective.com/arviz
Project-URL: source, https://github.com/arviz-devs/arviz-stats
Project-URL: tracker, https://github.com/arviz-devs/arviz-stats/issues
Provides-Extra: doc
Provides-Extra: numba
Provides-Extra: test
Provides-Extra: test-xarray
Provides-Extra: xarray

# arviz-stats

[![Run tests](https://github.com/arviz-devs/arviz-stats/actions/workflows/test.yml/badge.svg)](https://github.com/arviz-devs/arviz-stats/actions/workflows/test.yml)
[![codecov](https://codecov.io/gh/arviz-devs/arviz-stats/branch/main/graph/badge.svg?token=95N0B8O005)](https://codecov.io/gh/arviz-devs/arviz-stats)
[![Powered by NumFOCUS](https://img.shields.io/badge/powered%20by-NumFOCUS-orange.svg?style=flat&colorA=E1523D&colorB=007D8A)](https://numfocus.org)


ArviZ (pronounced "AR-_vees_") is a Python package for exploratory analysis of Bayesian models. It includes functions for posterior analysis, data storage, model checking, comparison and diagnostics.

arviz-stats is the subpackage in charge of the statistical and diagnostics computations.

### ArviZ in other languages
ArviZ also has a Julia wrapper available [ArviZ.jl](https://julia.arviz.org/).

## Documentation

The ArviZ documentation can be found in the [official docs](https://python.arviz.org).
Here are some quick links for common scenarios:

* First time Bayesian modelers and ArviZ users: [EABM book](https://arviz-devs.github.io/EABM/)
* First time ArviZ users, already familiar with Bayesian modeling: [overview notebook](https://python.arviz.org/projects/plots/en/latest/tutorials/overview.html) or [example gallery](https://python.arviz.org/projects/plots/en/latest/gallery/index.html)
* ArviZ 0.x user: [migration guide](https://python.arviz.org/en/latest/user_guide/migration_guide.html)
* ArviZ-verse documentation:
  - [arviz-base](https://python.arviz.org/projects/base/en/latest/)
  - [arviz-stats](https://python.arviz.org/projects/stats/en/latest/) (this package)
  - [arviz-plots](https://python.arviz.org/projects/plots/en/latest/)


## Installation

### Stable
ArviZ is available for installation from [PyPI](https://pypi.org/project/arviz/).
The latest stable version can be installed using pip:

```
pip install "arviz-stats[xarray]"
```

Note that it is also possible to install arviz-stats without the [xarray]. Doing that will install a minimal package, which only depends on numpy and scipy. Consequently, the functions that take arrays as inputs will be available, but many features won’t be available.

This is mostly aimed at advanced users or libraries that want to use ArviZ to compute diagnostics and statistical summaries but don’t want to depend on xarray.

### Development
The latest development version can be installed from the main branch using pip:

```
pip install git+git://github.com/arviz-devs/arviz-stats.git
```

Another option is to clone the repository and install using git and setuptools:

```
git clone https://github.com/arviz-devs/arviz-stats.git
cd arviz-stats
python setup.py install
```

## Citation


If you use ArviZ and want to cite it please use [![DOI](https://joss.theoj.org/papers/10.21105/joss.09889/status.svg)](https://doi.org/10.21105/joss.09889)

Here is the citation in BibTeX format

```
@article{Martin2026,
doi = {10.21105/joss.09889},
url = {https://doi.org/10.21105/joss.09889},
year = {2026},
publisher = {The Open Journal},
volume = {11},
number = {119},
pages = {9889},
author = {Martin, Osvaldo A. and Abril-Pla, Oriol and Deklerk, Jordan and Axen, Seth D. and Carroll, Colin and Hartikainen, Ari and Vehtari, Aki},
title = {ArviZ: a modular and flexible library for exploratory analysis of Bayesian models},
journal = {Journal of Open Source Software}}
```


## Contributions
ArviZ is a community project and welcomes contributions.
Additional information can be found in the [contributing guide](https://python.arviz.org/en/latest/contributing/index.html)


## Code of Conduct
ArviZ wishes to maintain a positive community. Additional details
can be found in the [Code of Conduct](https://www.arviz.org/en/latest/CODE_OF_CONDUCT.html)

## Donations
ArviZ is a non-profit project under NumFOCUS umbrella. If you want to support ArviZ financially, you can donate [here](https://numfocus.org/donate-to-arviz).

## Sponsors and Institutional Partners
[![Aalto University](https://raw.githubusercontent.com/arviz-devs/arviz-project/refs/heads/main/cards/Aalto-black-text.png)](https://www.aalto.fi/en)
[![FCAI](https://raw.githubusercontent.com/arviz-devs/arviz-project/refs/heads/main/cards/FCAI.png)](https://fcai.fi/)
[![NumFOCUS](https://raw.githubusercontent.com/arviz-devs/arviz-project/refs/heads/main/sphinx/NumFocus.png)](https://numfocus.org)

[The ArviZ project website](https://www.arviz.org/en/latest/sponsors_partners.html) has more information about each sponsor and the support they provide.

