diff --git a/cxx/clean_relation.hh b/cxx/clean_relation.hh
index e5625d3..0131c6f 100644
--- a/cxx/clean_relation.hh
+++ b/cxx/clean_relation.hh
@@ -518,7 +518,7 @@ class CleanRelation : public Relation<T> {
     }
   }
 
-  ValueType nearest(const ValueType& x, const T_items& items, std::mt19937* prng) const {
+  ValueType nearest(std::mt19937* prng, const ValueType& x, const T_items& items) const {
     std::vector<int> z = get_cluster_assignment(items);
     if (clusters.contains(z)) {
       return clusters.at(z)->nearest(x);
diff --git a/cxx/clean_relation_test.cc b/cxx/clean_relation_test.cc
index 3fa2d08..895a7e6 100644
--- a/cxx/clean_relation_test.cc
+++ b/cxx/clean_relation_test.cc
@@ -35,7 +35,7 @@ BOOST_AUTO_TEST_CASE(test_clean_relation) {
   BOOST_TEST(z1[0] == 0);
   BOOST_TEST(z1[1] == 0);
   BOOST_TEST(z1[2] == 0);
-  BOOST_TEST(R1.nearest(1, {1, 1, 3}, &prng) == 1);
+  BOOST_TEST(R1.nearest(&prng, 1, {1, 1, 3}) == 1);
 
   auto z2 = R1.get_cluster_assignment_gibbs({0, 1, 3}, D2, 1, 191);
   BOOST_TEST(z2.size() == 3);
@@ -222,6 +222,6 @@ BOOST_AUTO_TEST_CASE(test_nearest) {
   R1.incorporate(&prng, {1, 1}, "911");
   R1.incorporate(&prng, {2, 2}, "8675309");
 
-  BOOST_TEST(R1.nearest("1234", {0, 1}, &prng) == "1234");
-  BOOST_TEST(R1.nearest("jj9jddd322", {1, 2}, &prng) == "9322");
+  BOOST_TEST(R1.nearest(&prng, "1234", {0, 1}) == "1234");
+  BOOST_TEST(R1.nearest(&prng, "jj9jddd322", {1, 2}) == "9322");
 }
diff --git a/cxx/noisy_relation_test.cc b/cxx/noisy_relation_test.cc
index 7e5bd93..628138d 100644
--- a/cxx/noisy_relation_test.cc
+++ b/cxx/noisy_relation_test.cc
@@ -45,7 +45,7 @@ BOOST_AUTO_TEST_CASE(test_noisy_relation) {
   BOOST_TEST(z1[0] == 0);
   BOOST_TEST(z1[1] == 0);
   BOOST_TEST(z1[2] == 0);
-  BOOST_TEST(NR1.nearest(1, {1, 1, 3}, &prng) == 1);
+  BOOST_TEST(NR1.nearest(&prng, 1, {1, 1, 3}) == 1);
 
   double lpg __attribute__((unused));
   lpg = NR1.logp_gibbs_approx(D1, 0, 1, &prng);
@@ -73,7 +73,7 @@ BOOST_AUTO_TEST_CASE(test_noisy_relation) {
   NR2.set_cluster_assignment_gibbs(D3, 3, 1, &prng);
   D1.set_cluster_assignment_gibbs(0, 1);
 
-  BOOST_TEST(NR2.nearest("cat", {1, 3}, &prng) == "cat");
+  BOOST_TEST(NR2.nearest(&prng, "cat", {1, 3}) == "cat");
 }
 
 BOOST_AUTO_TEST_CASE(test_unincorporate) {
diff --git a/cxx/relation.hh b/cxx/relation.hh
index ef48d68..f3f090d 100644
--- a/cxx/relation.hh
+++ b/cxx/relation.hh
@@ -133,7 +133,7 @@ class Relation {
 
   // Return the value nearest to x that has non-zero probability under the
   // Relation's distribution for the items.
-  virtual ValueType nearest(const ValueType& x, const T_items& items, std::mt19937* prng) const {
+  virtual ValueType nearest(std::mt19937* prng, const ValueType& x, const T_items& items) const {
     return x;
   };
 
diff --git a/cxx/transition_latent_value.hh b/cxx/transition_latent_value.hh
index 6354ef7..7e7338e 100644
--- a/cxx/transition_latent_value.hh
+++ b/cxx/transition_latent_value.hh
@@ -58,7 +58,7 @@ void transition_latent_value(
       // > 0 probability.  A better solution would involve rewritting the
       // propose_clean methods to take the base_relation's Distribution as
       // a parameter.
-      candidate = base_relation->nearest(candidate, base_items, prng);
+      candidate = base_relation->nearest(prng, candidate, base_items);
       latent_value_candidates.push_back(candidate);
     }
   }