Add MvNormal moment

pymc/distributions/multivariate.py

@@ -224,6 +224,9 @@ def dist(cls, mu, cov=None, tau=None, chol=None, lower=True, **kwargs):
         cov = quaddist_matrix(cov, chol, tau, lower)
         return super().dist([mu, cov], **kwargs)
 
+    def get_moment(rv, size, mu, cov):
+        return mu
+
     def logp(value, mu, cov):
         """
         Calculate log-probability of Multivariate Normal distribution

pymc/tests/test_distributions_moments.py

@@ -36,6 +36,7 @@
     ZeroInflatedBinomial,
     ZeroInflatedPoisson,
 )
+from pymc.distributions.multivariate import MvNormal
 from pymc.distributions.shape_utils import rv_size_is_none
 from pymc.initial_point import make_initial_point_fn
 from pymc.model import Model
@@ -595,3 +596,16 @@ def test_discrete_uniform_moment(lower, upper, size, expected):
     with Model() as model:
         DiscreteUniform("x", lower=lower, upper=upper, size=size)
     assert_moment_is_expected(model, expected)
+
+
+@pytest.mark.parametrize(
+    "mu, cov, size, expected",
+    [
+        (np.array([1.]), np.array([[1.]]), None, np.array([1.])),
+        (np.ones((10, )), np.identity(10), None, np.ones((10, )))
+    ]
+)
+def test_mv_normal_moment(mu, cov, size, expected):
+    with Model() as model:
+        MvNormal("x", mu=mu, cov=cov, size=size)
+    assert_moment_is_expected(model, expected)