#537

chainladder/adjustments/berqsherm.py

@@ -140,6 +140,12 @@ def fit(self, X, y=None, sample_weight=None):
                 )
                 - 1
             )
+
+        # Don't allow lookup values beyond the final value.
+        n = min(lookup.shape[-1], lookup.shape[-2])
+        for j in range(n - 1):
+            lookup[:, :, j, :] = np.clip(lookup[:, :, j, :], 0,  n - j - 2)
+
         a = (
             xp.concatenate(
                 [

chainladder/adjustments/tests/test_berqsherm.py

@@ -17,3 +17,27 @@ def test_preserve_diagonal():
         == 0
     )
     assert berq_triangle != triangle
+
+def test_adjusted_values():
+    triangle = cl.load_sample("berqsherm").loc["MedMal"]
+    xp = triangle.get_array_module()
+    berq = cl.BerquistSherman(
+        paid_amount="Paid",
+        incurred_amount="Incurred",
+        reported_count="Reported",
+        closed_count="Closed",
+        trend=0.15,
+    )
+    berq_triangle = berq.fit_transform(triangle)
+
+    assert np.allclose(
+        triangle["Reported"].values, berq_triangle["Reported"].values, equal_nan=True
+    )
+
+    # Ensure that the incurred, paid, and closed count columns are as expected
+    berq_triangle.values[np.isnan(berq_triangle.values)] = 0
+    assert np.isclose(
+        berq_triangle["Incurred"].values.sum(), 1126985253.661, atol=1e-2
+    )
+    assert np.isclose(berq_triangle["Paid"].values.sum(), 182046766.054, atol=1e-2)
+    assert np.isclose(berq_triangle["Closed"].values.sum(), 8798.982, atol=1e-2)