PreliZ
PreliZ: A tool-box for prior elicitation - Published in JOSS (2023)
Science Score: 98.0%
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✓CITATION.cff file
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✓codemeta.json file
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✓.zenodo.json file
Found .zenodo.json file -
✓DOI references
Found 6 DOI reference(s) in README and JOSS metadata -
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Links to: joss.theoj.org -
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✓JOSS paper metadata
Published in Journal of Open Source Software
Keywords
Keywords from Contributors
Repository
Exploring and eliciting probability distributions
Basic Info
- Host: GitHub
- Owner: arviz-devs
- License: apache-2.0
- Language: Python
- Default Branch: main
- Homepage: https://preliz.readthedocs.io
- Size: 43.3 MB
Statistics
- Stars: 145
- Watchers: 12
- Forks: 12
- Open Issues: 14
- Releases: 37
Topics
Metadata Files
README.md
Exploring and eliciting probability distributions
Overview
Prior elicitation refers to the process of transforming the knowledge of a particular domain into well-defined probability distributions. Specifying useful priors is a central aspect of Bayesian statistics. PreliZ is a Python package aimed at helping practitioners choose prior distributions by offering a set of tools for the various facets of prior elicitation. It covers a range of methods, from unidimensional prior elicitation on the parameter space to predictive elicitation on the observed space. The goal is to be compatible with probabilistic programming languages (PPL) in the Python ecosystem like PyMC and PyStan, while remaining agnostic of any specific PPL.
A good companion for PreliZ is PriorDB, a database of prior distributions for Bayesian analysis. It is a community-driven project that aims to provide a comprehensive collection of prior distributions for a wide range of models and applications.
The Zen of PreliZ
- Being open source, community-driven, diverse and inclusive.
- Avoid fully-automated solutions, keep the human in the loop.
- Separate tasks between humans and computers, so users can retain control of important decisions while numerically demanding, error-prone or tedious tasks are automatized.
- Prevent users to become overconfident in their own opinions.
- Easily integrate with other tools.
- Allow predictive elicitation.
- Having a simple and intuitive interface suitable for non-specialists in order to minimize cognitive biases and heuristics.
- Switching between different types of visualization such as kernel density estimates plots, quantile dotplots, histograms, etc.
- Being agnostic of the underlying probabilistic programming language.
- Being modular.
Documentation
The PreliZ documentation can be found in the official docs.
Installation
Last release
PreliZ is available for installation from PyPI. The latest version (base set of dependencies) can be installed using pip:
pip install preliz
To make use of the interactive features, you can install the optional dependencies:
- For JupyterLab:
pip install "preliz[full,lab]"
- For Jupyter Notebook:
pip install "preliz[full,notebook]"
PreliZ is also available through conda-forge.
conda install -c conda-forge preliz
Development
The latest development version can be installed from the main branch using pip:
pip install git+git://github.com/arviz-devs/preliz.git
Citation
If you find PreliZ useful in your work, we kindly request that you cite the following paper:
@article{Icazatti_2023,
author = {Icazatti, Alejandro and Abril-Pla, Oriol and Klami, Arto and Martin, Osvaldo A},
doi = {10.21105/joss.05499},
journal = {Journal of Open Source Software},
month = sep,
number = {89},
pages = {5499},
title = {{PreliZ: A tool-box for prior elicitation}},
url = {https://joss.theoj.org/papers/10.21105/joss.05499},
volume = {8},
year = {2023}
}
Contributions
PreliZ is a community project and welcomes contributions. Additional information can be found in the Contributing Readme
Code of Conduct
PreliZ wishes to maintain a positive community. Additional details can be found in the Code of Conduct
Donations
PreliZ, as other ArviZ-devs projects, is a non-profit project under the NumFOCUS umbrella. If you want to support PreliZ financially, you can donate here.
Sponsors
Owner
- Name: ArviZ
- Login: arviz-devs
- Kind: organization
- Website: https://www.arviz.org
- Twitter: arviz_devs
- Repositories: 31
- Profile: https://github.com/arviz-devs
JOSS Publication
PreliZ: A tool-box for prior elicitation
Authors
IMASL-CONICET. Universidad Nacional de San Luis. San Luis, Argentina
Independent Researcher, Spain, Department of Computer Science, University of Helsinki, Finland
Department of Computer Science, University of Helsinki, Finland
IMASL-CONICET. Universidad Nacional de San Luis. San Luis, Argentina
Editor
Olexandr Konovalov
Tags
Bayesian statistics prior elicitationCitation (CITATION.cff)
cff-version: "1.2.0"
authors:
- family-names: Icazatti
given-names: Alejandro
orcid: "https://orcid.org/0000-0003-1491-7330"
- family-names: Abril-Pla
given-names: Oriol
orcid: "https://orcid.org/0000-0002-1847-9481"
- family-names: Klami
given-names: Arto
orcid: "https://orcid.org/0000-0002-7950-1355"
- family-names: Martin
given-names: Osvaldo A
orcid: "https://orcid.org/0000-0001-7419-8978"
contact:
- family-names: Martin
given-names: Osvaldo A
orcid: "https://orcid.org/0000-0001-7419-8978"
doi: 10.5281/zenodo.8368516
message: If you use this software, please cite our article in the
Journal of Open Source Software.
preferred-citation:
authors:
- family-names: Icazatti
given-names: Alejandro
orcid: "https://orcid.org/0000-0003-1491-7330"
- family-names: Abril-Pla
given-names: Oriol
orcid: "https://orcid.org/0000-0002-1847-9481"
- family-names: Klami
given-names: Arto
orcid: "https://orcid.org/0000-0002-7950-1355"
- family-names: Martin
given-names: Osvaldo A
orcid: "https://orcid.org/0000-0001-7419-8978"
date-published: 2023-09-22
doi: 10.21105/joss.05499
issn: 2475-9066
issue: 89
journal: Journal of Open Source Software
publisher:
name: Open Journals
start: 5499
title: "PreliZ: A tool-box for prior elicitation"
type: article
url: "https://joss.theoj.org/papers/10.21105/joss.05499"
volume: 8
title: "PreliZ: A tool-box for prior elicitation"
GitHub Events
Total
- Create event: 7
- Release event: 8
- Issues event: 38
- Watch event: 55
- Member event: 1
- Issue comment event: 123
- Push event: 111
- Pull request review event: 101
- Pull request review comment event: 105
- Pull request event: 182
- Fork event: 5
Last Year
- Create event: 7
- Release event: 8
- Issues event: 38
- Watch event: 55
- Member event: 1
- Issue comment event: 123
- Push event: 111
- Pull request review event: 101
- Pull request review comment event: 105
- Pull request event: 182
- Fork event: 5
Committers
Last synced: 5 months ago
Top Committers
| Name | Commits | |
|---|---|---|
| Osvaldo A Martin | a****a@g****m | 393 |
| Alejandro Icazatti | a****i@g****m | 113 |
| Rohan Babbar | r****8@y****m | 58 |
| Oriol Abril-Pla | o****a@g****m | 6 |
| Nishant Rajadhyaksha | 7****1 | 3 |
| Christine P. Chai | s****p@g****m | 2 |
| pdb5627 | p****7 | 1 |
| Olexandr Konovalov | 5****v | 1 |
| Ari Hartikainen | a****n | 1 |
| Advait | 1****4 | 1 |
Issues and Pull Requests
Last synced: 4 months ago
All Time
- Total issues: 110
- Total pull requests: 626
- Average time to close issues: 3 months
- Average time to close pull requests: 1 day
- Total issue authors: 21
- Total pull request authors: 9
- Average comments per issue: 1.5
- Average comments per pull request: 0.73
- Merged pull requests: 573
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 27
- Pull requests: 233
- Average time to close issues: 9 days
- Average time to close pull requests: 1 day
- Issue authors: 11
- Pull request authors: 7
- Average comments per issue: 0.74
- Average comments per pull request: 0.68
- Merged pull requests: 207
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- aloctavodia (77)
- aleicazatti (5)
- rohanbabbar04 (4)
- jessegrabowski (3)
- djmannion (3)
- ricardoV94 (3)
- jungtaekkim (1)
- upandacross (1)
- williambdean (1)
- andins (1)
- random-walkie (1)
- ivaquero (1)
- hectormz (1)
- pdb5627 (1)
- OriolAbril (1)
Pull Request Authors
- aloctavodia (349)
- aleicazatti (138)
- rohanbabbar04 (116)
- nishant42491 (8)
- star1327p (5)
- OriolAbril (5)
- Advaitgaur004 (2)
- pdb5627 (2)
- olexandr-konovalov (1)
Top Labels
Issue Labels
Pull Request Labels
Packages
- Total packages: 1
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Total downloads:
- pypi 32,274 last-month
- Total dependent packages: 1
- Total dependent repositories: 3
- Total versions: 36
- Total maintainers: 2
pypi.org: preliz
Exploring and eliciting probability distributions.
- Documentation: https://preliz.readthedocs.io/
- License: Apache Software License
-
Latest release: 0.20.0
published 5 months ago
Rankings
Maintainers (2)
Dependencies
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