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Pymc bayesian modeler

Skill a5c-ai/babysitter/library/specializations/domains/science/physics/skills/pymc-bayesian-modeler

PyMC probabilistic programming skill for hierarchical Bayesian models in physics data analysisFrom its SKILL.md

Install
npx -y skills add a5c-ai/babysitter --skill pymc-bayesian-modeler

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

SKILL.md

1.3 KB, 163 tokens by cl100k_base, as published. Nobody here has run it

PyMC Bayesian Modeler

Purpose

Provides expert guidance on PyMC for Bayesian modeling in physics, including hierarchical models and advanced inference methods.

Capabilities

  • Probabilistic model construction
  • NUTS/HMC sampling
  • Variational inference
  • Gaussian processes
  • Model comparison (WAIC, LOO)
  • Prior predictive checks

Usage Guidelines

  1. Model Building: Construct probabilistic models
  2. Priors: Specify informative or weakly informative priors
  3. Sampling: Use NUTS for efficient sampling
  4. Diagnostics: Check convergence with trace plots and r-hat
  5. Comparison: Compare models with information criteria

Tools/Libraries

  • PyMC
  • arviz
  • Theano/JAX

What ships with it

Read from the repository

Just SKILL.md. No reference files, no scripts.

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