Probabilistic Modeling Quick Reference

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Using pymc, bambi, rstan, and rstanarm

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Purpose

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This project serves as a consolidated quick reference for sampling common probabilistic models in python and R. Many bayesian modeling techniques can be difficult to set up if you’re not doing them on a regular basis, and my hope is that having a couple templates set up in an approachable and ready to run format will make them more approachable in my day to day work

Dataset & Libraries

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The dataset used for the current project was pulled from the following:

• datasets R library
• scikit-learn python package

And the examples provided here were adapted from the documentation of the following modeling frameworks:

• pymc
• bambi
• rstan
• rstanarm

Outputs

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• RMarkdown notebook with rstan and rstanarm implementations
• Jupyter notebook and python script with pymc and bambi implementations