pymc-bayesian-modeling
Bayesian modeling with PyMC. Build hierarchical models, MCMC (NUTS), variational inference, LOO/WAIC comparison, posterior checks, for probabilistic programming and inference.
- Skills
- Scientific
- 2
What it does and how to use it
A skill that teaches Claude Code to do scientific tasks well. It is packaged knowledge the model uses whenever it is relevant.
- Install the skill (command above).
- In Claude Code, describe what you need - the skill turns on by itself when the context fits.
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Install (Claude Code)
mkdir -p .claude/skills/pymc-bayesian-modeling && curl -fsSL https://doutorai.pt/data/lib/skills__pymc-bayesian-modeling.md -o .claude/skills/pymc-bayesian-modeling/SKILL.mdPaste this command into the terminal, in your project folder, and the component installs automatically.
Content
---
name: pymc-bayesian-modeling
description: "Bayesian modeling with PyMC. Build hierarchical models, MCMC (NUTS), variational inference, LOO/WAIC comparison, posterior checks, for probabilistic programming and inference."
---
# PyMC Bayesian Modeling
## Overview
PyMC is a Python library for Bayesian modeling and probabilistic programming. Build, fit, validate, and compare Bayesian models using PyMC's modern API (version 5.x+), including hierarchical models, MCMC sampling (NUTS), variational inference, and model comparison (LOO, WAIC).
## When to Use This Skill
This skill should be used
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