arviz 1.0.0

Expose features from _ArviZverse_ refactored packages together in the ``arviz`` namespace.

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 in other languages

ArviZ also has a Julia wrapper available ArviZ.jl.

Documentation

The ArviZ documentation can be found in the official docs. Here are some quick links for common scenarios:

• First time Bayesian modelers and ArviZ users: EABM book
• First time ArviZ users, already familiar with Bayesian modeling: overview notebook or example gallery
• ArviZ 0.x user: migration guide
• ArviZ-verse documentation:
  • arviz-base
  • arviz-stats
  • arviz-plots

Installation

Stable

ArviZ is available for installation from PyPI. The latest stable version can be installed using pip:

pip install "arviz[preview]"

ArviZ is also available through conda-forge.

conda install -c conda-forge arviz arviz-plots

Development

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

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

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

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

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Gallery

And more...

Citation

If you use ArviZ and want to cite it please use

Here is the citation in BibTeX format

@article{arviz_2019,
  doi = {10.21105/joss.01143},
  url = {https://doi.org/10.21105/joss.01143},
  year = {2019},
  publisher = {The Open Journal},
  volume = {4},
  number = {33},
  pages = {1143},
  author = {Ravin Kumar and Colin Carroll and Ari Hartikainen and Osvaldo Martin},
  title = {ArviZ a unified library for exploratory analysis of Bayesian models in Python},
  journal = {Journal of Open Source Software}
}

Contributions

ArviZ is a community project and welcomes contributions. Additional information can be found in the contributing guide

Code of Conduct

ArviZ wishes to maintain a positive community. Additional details can be found in the Code of Conduct

Donations

ArviZ is a non-profit project under NumFOCUS umbrella. If you want to support ArviZ financially, you can donate here.

Sponsors and Institutional Partners

The ArviZ project website has more information about each sponsor and the support they provide.