a5c-ai/pymc-bayesian-modeler
library/specializations/domains/science/physics/skills/pymc-bayesian-modeler/SKILL.md
PyMC probabilistic programming skill for hierarchical Bayesian models in physics data analysis
$ install --global
skillsauthnpx skillsauth add a5c-ai/babysitter pymc-bayesian-modelerInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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SKILL.md
- name:
- pymc-bayesian-modeler
- description:
- PyMC probabilistic programming skill for hierarchical Bayesian models in physics data analysis
- specialization:
- physics
- domain:
- science
- category:
- data-analysis
- phase:
- 6
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
- Model Building: Construct probabilistic models
- Priors: Specify informative or weakly informative priors
- Sampling: Use NUTS for efficient sampling
- Diagnostics: Check convergence with trace plots and r-hat
- Comparison: Compare models with information criteria
Tools/Libraries
- PyMC
- arviz
- Theano/JAX
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