pymc-bayesian-modeling
✓Bayesian modeling with PyMC. Build hierarchical models, MCMC (NUTS), variational inference, LOO/WAIC comparison, posterior checks, for probabilistic programming and inference.
Installation
SKILL.md
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).
Critical: Always use non-centered parameterization for hierarchical models to avoid divergences.
See: references/distributions.md for comprehensive distribution reference
Bayesian modeling with PyMC. Build hierarchical models, MCMC (NUTS), variational inference, LOO/WAIC comparison, posterior checks, for probabilistic programming and inference. Source: jackspace/claudeskillz.
Facts (cite-ready)
Stable fields and commands for AI/search citations.
- Install command
npx skills add https://github.com/jackspace/claudeskillz --skill pymc-bayesian-modeling- Source
- jackspace/claudeskillz
- Category
- </>Dev Tools
- Verified
- ✓
- First Seen
- 2026-02-17
- Updated
- 2026-02-18
Quick answers
What is pymc-bayesian-modeling?
Bayesian modeling with PyMC. Build hierarchical models, MCMC (NUTS), variational inference, LOO/WAIC comparison, posterior checks, for probabilistic programming and inference. Source: jackspace/claudeskillz.
How do I install pymc-bayesian-modeling?
Open your terminal or command line tool (Terminal, iTerm, Windows Terminal, etc.) Copy and run this command: npx skills add https://github.com/jackspace/claudeskillz --skill pymc-bayesian-modeling Once installed, the skill will be automatically configured in your AI coding environment and ready to use in Claude Code or Cursor
Where is the source repository?
https://github.com/jackspace/claudeskillz
Details
- Category
- </>Dev Tools
- Source
- skills.sh
- First Seen
- 2026-02-17