R Academy · Lesson

Writing Stan Models in R

Define data blocks, parameters, and the model block in Stan syntax.

What Is Stan?

Stan is a probabilistic programming language for Bayesian statistical modelling. RStan is the R interface to Stan. You write the model in Stan's language (C++-like), and Stan compiles it to efficient C++ code that runs Hamiltonian Monte Carlo (HMC) sampling to approximate the posterior.

# Stan installation check
library(rstan)

# Check version
cat('RStan version:', as.character(packageVersion('rstan')), '\n')

# Enable parallel chains
options(mc.cores = parallel::detectCores())

# Reuse compiled models across sessions
rstan_options(auto_write = TRUE)

cat('Stan ready. Cores:', parallel::detectCores(), '\n')

Stan Model Structure

A Stan model has up to six named blocks: data, transformed data, parameters, transformed parameters, model, and generated quantities. The three essential blocks are data, parameters, and model.

library(rstan)

# Stan model as a character string in R
stan_code <- '
data {
  int<lower=0> N;       // number of observations
  vector[N] x;          // predictor
  vector[N] y;          // response
}
parameters {
  real alpha;           // intercept
  real beta;            // slope
  real<lower=0> sigma;  // noise (must be positive)
}
model {
  // Priors
  alpha ~ normal(0, 10);
  beta  ~ normal(0, 10);
  sigma ~ exponential(1);

  // Likelihood
  y ~ normal(alpha + beta * x, sigma);
}
'

cat('Stan model defined as a string in R\n')
cat('Blocks: data, parameters, model\n')

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