https://github.com/arviz-devs/eabm

Source repository for the online book Exploratory Analysis of Bayesian Models.

https://github.com/arviz-devs/eabm

Science Score: 49.0%

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optimizing-compiler closember statistical-modeling variational-inference bayesian-inference mcmc probabilistic-programming pytensor statistical-analysis regression-models
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Repository

Source repository for the online book Exploratory Analysis of Bayesian Models.

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  • Stars: 24
  • Watchers: 12
  • Forks: 14
  • Open Issues: 5
  • Releases: 2
Created over 7 years ago · Last pushed 7 months ago
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Readme License

README.md

Exploratory Analysis of Bayesian Models

This is the code repository for the online book Exploratory Analysis of Bayesian Models.

Preface

When working with Bayesian models there are a series of related tasks that need to be addressed besides inference itself:

  • Diagnoses of the quality of the inference (as this is generally done using numerical approximation methods)
  • Model criticism, including evaluations of both model assumptions and model predictions
  • Comparison of models, including model selection or model averaging
  • Preparation of the results for a particular audience

We collectively call all these tasks Exploratory analysis of Bayesian models, building on concepts from Exploratory data analysis to examine and gain deeper insights into Bayesian models.

In the words of Persi Diaconis:

"Exploratory data analysis seeks to reveal structure, or simple descriptions in data. We look at numbers or graphs and try to find patterns. We pursue leads suggested by background information, imagination, patterns perceived, and experience with other data analyses".

In this book, we discuss how to use both numerical and visual summaries to successfully perform the many tasks that are central to the iterative and interactive modeling process. To do so, we first discuss some general principles of data visualization and uncertainty representation that are not exclusive to Bayesian statistics.

Citations

If you are using specific methods or functions from the book, please consider citing the scientific paper and/or corresponding package.

If you want to cite this online book in your research. The following citation is recommended, as it always resolves to the latest version of the book:

Martin et al. (2025). Exploratory Analysis of Bayesian Models. Zenodo. https://zenodo.org/records/15127549

You can use the following BibTeX entry:

@book{eabm_2025, author = {Osvaldo A Martin and Oriol Abril-Pla}, title = {Exploratory analysis of Bayesian models}, month = apr, year = 2025, publisher = {Zenodo}, version = {v0.2.0}, doi = {10.5281/zenodo.15127549}, url = {https://doi.org/10.5281/zenodo.15127549}, },

Donations

If you find this book useful, please consider supporting the authors by making a donation. This will help us to keep the book updated and to provide more resources in the future.

License

This book is licensed under the CC-BY-NC 4.0. License. See the LICENSE file for details.

Owner

  • Name: ArviZ
  • Login: arviz-devs
  • Kind: organization

GitHub Events

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Last Year
  • Create event: 1
  • Issues event: 6
  • Release event: 2
  • Watch event: 4
  • Issue comment event: 2
  • Push event: 68
  • Pull request review event: 5
  • Pull request event: 69
  • Fork event: 3

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Last synced: 11 months ago

All Time
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  • Total Committers: 8
  • Avg Commits per committer: 18.125
  • Development Distribution Score (DDS): 0.172
Past Year
  • Commits: 101
  • Committers: 5
  • Avg Commits per committer: 20.2
  • Development Distribution Score (DDS): 0.069
Top Committers
Name Email Commits
Osvaldo A Martin a****a@g****m 120
Ravin Kumar r****e@g****m 13
Oriol Abril-Pla o****a@g****m 4
dependabot[bot] 4****] 3
Christine P. Chai s****p@g****m 2
rpgoldman r****n@g****g 1
Ognjen Stefanović s****1@g****m 1
Alexandre Andorra a****e@g****m 1
Committer Domains (Top 20 + Academic)

Issues and Pull Requests

Last synced: 7 months ago

All Time
  • Total issues: 15
  • Total pull requests: 158
  • Average time to close issues: over 3 years
  • Average time to close pull requests: 21 days
  • Total issue authors: 3
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  • Average comments per issue: 0.33
  • Average comments per pull request: 0.61
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  • Issue authors: 3
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  • Average comments per issue: 0.0
  • Average comments per pull request: 0.08
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  • canyon289 (7)
  • OriolAbril (6)
  • dependabot[bot] (3)
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dependencies (3)

Dependencies

.github/workflows/publish.yml actions
  • actions/checkout v4 composite
  • actions/setup-python v4 composite
  • quarto-dev/quarto-actions/publish v2 composite
  • quarto-dev/quarto-actions/setup v2 composite
requirements.txt pypi
  • arviz ==0.16.1
  • preliz ==0.3.3