pymc-fundamentals
CommunityMaster PyMC 5 modeling with fundamentals.
Authorchoxos
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This skill provides foundational knowledge for writing and reviewing PyMC 5 models, guiding users through syntax, priors, likelihoods, sampling, and ArviZ diagnostics to ensure correct Bayesian workflows.
Core Features & Use Cases
- Model construction: Define priors, likelihoods, and deterministic relationships in PyMC 5.
- Sampling & diagnostics: Run MCMC sampling and interpret ArviZ outputs to assess convergence and fit.
- Model conversion: Translate models from Stan/JAGS to PyMC and compare results.
Quick Start
Create a simple PyMC 5 model with a Normal prior and run a short MCMC sample to obtain the posterior trace.
Dependency Matrix
Required Modules
None requiredComponents
Standard package💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: pymc-fundamentals Download link: https://github.com/choxos/BiostatAgent/archive/main.zip#pymc-fundamentals Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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