diff --git a/notas/src/heart-agregado.stan b/notas/src/heart-agregado.stan
new file mode 100644
index 0000000..85c60a7
--- /dev/null
+++ b/notas/src/heart-agregado.stan
@@ -0,0 +1,30 @@
+data {
+  int<lower=0> N;
+  array[N]  int e;
+  array[N]  int y;
+}
+
+parameters {
+  real <lower=0> lambda;
+}
+
+transformed parameters {
+  vector[N] media_hospital;
+  // lambda es por cada 1000 expuestos:
+  for (i in 1:N){
+    media_hospital[i] = lambda * e[i] / 1000;
+  }
+}
+
+model {
+  // partes no determinísticas
+  y ~ poisson(media_hospital);
+  lambda ~ exponential(1);
+}
+
+generated quantities {
+  array[N] int y_sim;
+  for (i in 1:N){
+    y_sim[i] = poisson_rng(media_hospital[i]);
+  }
+}
diff --git a/notas/src/heart-individual.stan b/notas/src/heart-individual.stan
new file mode 100644
index 0000000..7fd6376
--- /dev/null
+++ b/notas/src/heart-individual.stan
@@ -0,0 +1,30 @@
+data {
+  int<lower=0> N;
+  array[N]  int e;
+  array[N]  int y;
+}
+
+parameters {
+  vector<lower=0>[N] lambda;
+}
+
+transformed parameters {
+  vector[N] media_hospital;
+  // lambda es por cada 1000 expuestos:
+  for (i in 1:N){
+    media_hospital[i] = lambda[i] * e[i] / 1000;
+  }
+}
+
+model {
+  // partes no determinísticas
+  y ~ poisson(media_hospital);
+  lambda ~ exponential(1);
+}
+
+generated quantities {
+  array[N] int y_sim;
+  for (i in 1:N){
+    y_sim[i] = poisson_rng(media_hospital[i]);
+  }
+}
diff --git a/notas/src/heart-jerarquico.stan b/notas/src/heart-jerarquico.stan
new file mode 100644
index 0000000..1684aa3
--- /dev/null
+++ b/notas/src/heart-jerarquico.stan
@@ -0,0 +1,34 @@
+data {
+  int<lower=0> N;
+  array[N]  int e;
+  array[N]  int y;
+}
+
+parameters {
+  vector<lower=0>[N] lambda;
+  real<lower=0> alpha;
+  real<lower=0> mu;
+}
+
+transformed parameters {
+  vector[N] media_hospital;
+  // lambda es por cada 1000 expuestos:
+  for (i in 1:N){
+    media_hospital[i] = lambda[i] * e[i] /1000;
+  }
+}
+
+model {
+  // partes no determinísticas
+  y ~ poisson(media_hospital);
+  lambda ~ gamma(alpha, alpha / mu);
+  mu ~ exponential(1);
+  alpha ~ exponential(1);
+}
+
+generated quantities {
+  array[N] int y_sim;
+  for (i in 1:N){
+    y_sim[i] = poisson_rng(media_hospital[i]);
+  }
+}