diff --git a/target_densities/multi-logit-normal.stan b/target_densities/multi-logit-normal.stan
new file mode 100644
index 0000000..af97e42
--- /dev/null
+++ b/target_densities/multi-logit-normal.stan
@@ -0,0 +1,30 @@
+// PASTE INTO functions { ... } to define densities
+
+  /**
+   * Return the multivariate logistic normal density for the specified log simplex.
+   *
+   * See: https://en.wikipedia.org/wiki/Logit-normal_distribution#Multivariate_generalization
+   * 
+   * @param theta a log simplex (N rows)
+   * @param mu location of normal (N-1 rows)
+   * @param L_Sigma Cholesky factor of covariance (N-1 rows, N-1 cols)
+   */
+  real multi_log_logit_normal_cholesky_lpdf(vector log_theta, vector mu, matrix L_Sigma) {
+    int N = rows(log_theta);     
+    return multi_normal_cholesky_lpdf(log_theta[1:N-1] - log_theta[N] | mu, L_Sigma);
+  }
+
+  /**
+   * Return the multivariate logistic normal density for the specified simplex.
+   *
+   * See: https://en.wikipedia.org/wiki/Logit-normal_distribution#Multivariate_generalization
+   * 
+   * @param theta a simplex (N rows)
+   * @param mu location of normal (N-1 rows)
+   * @param L_Sigma Cholesky factor of covariance (N-1 rows, N-1 cols)
+   */
+  real multi_logit_normal_cholesky_lpdf(vector theta, vector mu, matrix L_Sigma) {
+    vector[rows(theta)] log_theta = log(theta);
+    return sum(-log_theta)
+      + multi_log_logit_normal_cholesky_lpdf(log_theta | mu, L_Sigma);
+  }