--- a
+++ b/inst/stan/base0_logit.stan
@@ -0,0 +1,36 @@
+//
+// Gaussian prior on regression coeffs (logistic regression)
+//
+
+data {
+
+  // number of unpenalized columns in model matrix
+  int U;
+
+  // number of observations
+  int N;
+
+  // prior standard deviation for the unpenalised variables
+  real <lower=0> scale_u;
+
+  // design matrix
+  matrix[N, U] X;
+
+  // binary response variable
+  array[N] int<lower=0, upper=1> y;
+}
+
+parameters {
+
+  // unpenalized regression parameters
+  vector[U] beta_u;
+}
+
+model {
+
+  // unpenalized coefficients including intercept
+  beta_u ~ normal(0, scale_u);
+
+  // likelihood
+  y ~ bernoulli_logit_glm(X, 0, beta_u);
+}