diff --git a/ezyrb/reducedordermodel.py b/ezyrb/reducedordermodel.py
index 8f654ab..cdcb228 100644
--- a/ezyrb/reducedordermodel.py
+++ b/ezyrb/reducedordermodel.py
@@ -217,15 +217,16 @@ class ReducedOrderModel():
         db_range = list(range(len(self.database)))
 
         for j in db_range:
-            remaining_index = db_range[:]
-            remaining_index.remove(j)
-            new_db = self.database[remaining_index]
+            indeces = np.array([True] * len(self.database))
+            indeces[j] = False
+
+            new_db = self.database[indeces]
+            test_db = self.database[~indeces]
             rom = type(self)(new_db, copy.deepcopy(self.reduction),
                              copy.deepcopy(self.approximation)).fit(
                                  *args, **kwargs)
 
-            error[j] = norm(self.database.snapshots[j] -
-                            rom.predict(self.database.parameters[j]))
+            error[j] = rom.test_error(test_db)
 
         return error
 

diff --git a/tests/test_reducedordermodel.py b/tests/test_reducedordermodel.py
index 788bae6..7a94432 100644
--- a/tests/test_reducedordermodel.py
+++ b/tests/test_reducedordermodel.py
@@ -177,7 +177,7 @@ class TestReducedOrderModel(TestCase):
         err = rom.loo_error()
         np.testing.assert_allclose(
             err,
-            np.array([421.299091, 344.571787,  48.711501, 300.490491]),
+            np.array([0.540029, 1.211744, 0.271776, 0.919509]),
             rtol=1e-4)
 
     def test_loo_error_02(self):
@@ -188,7 +188,7 @@ class TestReducedOrderModel(TestCase):
         err = rom.loo_error(normalizer=False)
         np.testing.assert_allclose(
             err[0],
-            np.array(498.703803),
+            np.array(0.639247),
             rtol=1e-3)
 
     def test_loo_error_singular_values(self):
@@ -206,5 +206,5 @@ class TestReducedOrderModel(TestCase):
         db = Database(param, snapshots.T)
         rom = ROM(db, pod, rbf).fit()
         opt_mu = rom.optimal_mu()
-        np.testing.assert_allclose(opt_mu, [[-0.17687147, -0.21820951]],
+        np.testing.assert_allclose(opt_mu, [[-0.046381, -0.15578 ]],
             rtol=1e-4)

LOO error is an absolute error
loo_error in reducedordermodel.py is an absolute error.
tests/test_reducedordermodel.py::TestReducedOrderModel::test_loo_error_01 tests/test_reducedordermodel.py::TestReducedOrderModel::test_loo_error_02 tests/test_reducedordermodel.py::TestReducedOrderModel::test_optimal_mu
tests/test_reducedordermodel.py::TestReducedOrderModel::test_constructor tests/test_reducedordermodel.py::TestReducedOrderModel::test_kfold_cv_error_01 tests/test_reducedordermodel.py::TestReducedOrderModel::test_load tests/test_reducedordermodel.py::TestReducedOrderModel::test_load2 tests/test_reducedordermodel.py::TestReducedOrderModel::test_loo_error_singular_values tests/test_reducedordermodel.py::TestReducedOrderModel::test_predict_01 tests/test_reducedordermodel.py::TestReducedOrderModel::test_predict_02 tests/test_reducedordermodel.py::TestReducedOrderModel::test_predict_03 tests/test_reducedordermodel.py::TestReducedOrderModel::test_predict_04 tests/test_reducedordermodel.py::TestReducedOrderModel::test_predict_scaler_01 tests/test_reducedordermodel.py::TestReducedOrderModel::test_predict_scaler_02 tests/test_reducedordermodel.py::TestReducedOrderModel::test_predict_scaling_coeffs tests/test_reducedordermodel.py::TestReducedOrderModel::test_save tests/test_reducedordermodel.py::TestReducedOrderModel::test_test_error