MCMC Sampling with Stan

Overview

This skill provides procedural guidance for implementing Markov Chain Monte Carlo (MCMC) sampling using Stan and RStan. It covers the complete workflow from environment setup through model specification to convergence validation, with emphasis on avoiding common pitfalls in hierarchical Bayesian modeling.

When to Use This Skill

• Installing and configuring RStan in R environments
• Writing Stan models for Bayesian inference
• Implementing hierarchical/multilevel models
• Configuring MCMC sampling parameters
• Diagnosing and validating MCMC convergence

Pre-Implementation Checklist

Before writing any code, verify the following in order:

1. System Dependencies First