Eight schools noncentered model in PyMC

posterior_database/models/info/eight_schools_noncentered.info.json

@@ -13,8 +13,9 @@
       "model_code": "models/stan/eight_schools_noncentered.stan",
       "stan_version": ">=2.26.0"
     },
-    "pymc3": {
-      "model_code": "models/pymc3/eight_schools_noncentered.py"
+    "pymc": {
+      "model_code": "models/pymc/eight_schools_noncentered.py",
+      "pymc_version": ">=5.16.2" 
     }
   },
   "added_by": "Mans Magnusson",

posterior_database/models/pymc/eight_schools_noncentered.py

@@ -0,0 +1,18 @@
+import numpy as np
+import pymc as pm
+
+
+def model(data):
+    y_obs = np.array(data["y"])  # estimated treatment
+    sigma = np.array(data["sigma"])  # std of estimated effect
+    coords = {"school": np.arange(data["J"])}
+    with pm.Model(coords=coords) as pymc_model:
+
+        mu = pm.Normal(
+            "mu", mu=0, sigma=5
+        )  # hyper-parameter of mean, non-informative prior
+        tau = pm.HalfCauchy("tau", beta=5)  # hyper-parameter of sigma
+        theta_trans = pm.Normal("theta_trans", mu=0, sigma=1, dims="school")
+        theta = mu + tau * theta_trans
+        y = pm.Normal("y", mu=theta, sigma=sigma, observed=y_obs)
+    return pymc_model