peel out stan code

Author: m-clark

regression_model_example.stan

@@ -0,0 +1,33 @@
+data {                      // Data block
+  int<lower=1> N;           // Sample size
+  int<lower=1> K;           // Dimension of model matrix
+  matrix[N, K] X;           // Model Matrix
+  vector[N] y;              // Target variable
+}
+
+/*
+transformed data {          // Transformed data block. Not used presently.
+}
+*/
+
+parameters {                // Parameters block
+  vector[K] beta;           // Coefficient vector
+  real<lower=0> sigma;      // Error scale
+}
+
+model {                     // Model block
+  vector[N] mu;
+  mu = X * beta;            // Creation of linear predictor
+
+  // priors
+  beta ~ normal(0, 10);
+  sigma ~ cauchy(0, 5);     // With sigma bounded at 0, this is half-cauchy
+
+  // likelihood
+  y ~ normal(mu, sigma);
+}
+
+/*
+generated quantities {      // Generated quantities block. Not used presently.
+}
+*/

regression_model_example_2.stan

@@ -0,0 +1,40 @@
+data {                      // Data block
+  int<lower=1> N;           // Sample size
+  int<lower=1> K;           // Dimension of model matrix
+  matrix [N, K] X;          // Model Matrix
+  vector[N] y;              // Target variable
+}
+
+/*
+transformed data {          // Transformed data block. Not used presently.
+}
+*/
+
+parameters {                // Parameters block; declarations only
+  vector[K] beta;           // Coefficient vector
+  real<lower=0> sigma;      // Error scale
+}
+
+model {                     // Model block
+  vector[N] mu;
+  mu <- X * beta;           // Creation of linear predictor
+
+  // priors
+  beta ~ normal(0, 10);
+  sigma ~ cauchy(0, 5);     // With sigma bounded at 0, this is half-cauchy
+
+  // likelihood
+  y ~ normal(mu, sigma);
+}
+
+generated quantities {
+  real rss;
+  real totalss;
+  real<lower=0, upper=1> R2;
+  vector[N] mu;
+
+  mu <- X * beta;
+  rss <- dot_self(y-mu);
+  totalss <- dot_self(y-mean(y));
+  R2 <- 1 - rss/totalss;
+}