diff --git a/gtsam/hybrid/HybridNonlinearFactor.h b/gtsam/hybrid/HybridNonlinearFactor.h
index d8e3990f0..742b4c162 100644
--- a/gtsam/hybrid/HybridNonlinearFactor.h
+++ b/gtsam/hybrid/HybridNonlinearFactor.h
@@ -33,6 +33,9 @@
 
 namespace gtsam {
 
+/// Alias for a NonlinearFactor shared pointer and double scalar pair.
+using NonlinearFactorValuePair = std::pair<NonlinearFactor::shared_ptr, double>;
+
 /**
  * @brief Implementation of a discrete conditional mixture factor.
  *
@@ -55,7 +58,7 @@ class HybridNonlinearFactor : public HybridFactor {
    * @brief typedef for DecisionTree which has Keys as node labels and
    * pairs of NonlinearFactor & an arbitrary scalar as leaf nodes.
    */
-  using Factors = DecisionTree<Key, std::pair<sharedFactor, double>>;
+  using Factors = DecisionTree<Key, NonlinearFactorValuePair>;
 
  private:
   /// Decision tree of Gaussian factors indexed by discrete keys.
@@ -100,8 +103,7 @@ class HybridNonlinearFactor : public HybridFactor {
       const std::vector<std::pair<std::shared_ptr<FACTOR>, double>>& factors,
       bool normalized = false)
       : Base(keys, discreteKeys), normalized_(normalized) {
-    std::vector<std::pair<NonlinearFactor::shared_ptr, double>>
-        nonlinear_factors;
+    std::vector<NonlinearFactorValuePair> nonlinear_factors;
     KeySet continuous_keys_set(keys.begin(), keys.end());
     KeySet factor_keys_set;
     for (auto&& [f, val] : factors) {
diff --git a/gtsam/hybrid/tests/Switching.h b/gtsam/hybrid/tests/Switching.h
index f799168f2..9b7c44d02 100644
--- a/gtsam/hybrid/tests/Switching.h
+++ b/gtsam/hybrid/tests/Switching.h
@@ -162,7 +162,7 @@ struct Switching {
     for (size_t k = 0; k < K - 1; k++) {
       KeyVector keys = {X(k), X(k + 1)};
       auto motion_models = motionModels(k, between_sigma);
-      std::vector<std::pair<NonlinearFactor::shared_ptr, double>> components;
+      std::vector<NonlinearFactorValuePair> components;
       for (auto &&f : motion_models) {
         components.push_back(
             {std::dynamic_pointer_cast<NonlinearFactor>(f), 0.0});
diff --git a/gtsam/hybrid/tests/testHybridBayesNet.cpp b/gtsam/hybrid/tests/testHybridBayesNet.cpp
index bf3301d2f..cf4231dba 100644
--- a/gtsam/hybrid/tests/testHybridBayesNet.cpp
+++ b/gtsam/hybrid/tests/testHybridBayesNet.cpp
@@ -387,8 +387,8 @@ TEST(HybridBayesNet, Sampling) {
       std::make_shared<BetweenFactor<double>>(X(0), X(1), 0, noise_model);
   auto one_motion =
       std::make_shared<BetweenFactor<double>>(X(0), X(1), 1, noise_model);
-  std::vector<std::pair<NonlinearFactor::shared_ptr, double>> factors = {
-      {zero_motion, 0.0}, {one_motion, 0.0}};
+  std::vector<NonlinearFactorValuePair> factors = {{zero_motion, 0.0},
+                                                   {one_motion, 0.0}};
   nfg.emplace_shared<PriorFactor<double>>(X(0), 0.0, noise_model);
   nfg.emplace_shared<HybridNonlinearFactor>(
       KeyVector{X(0), X(1)}, DiscreteKeys{DiscreteKey(M(0), 2)}, factors);
diff --git a/gtsam/hybrid/tests/testHybridEstimation.cpp b/gtsam/hybrid/tests/testHybridEstimation.cpp
index 76e5880ee..7204d819d 100644
--- a/gtsam/hybrid/tests/testHybridEstimation.cpp
+++ b/gtsam/hybrid/tests/testHybridEstimation.cpp
@@ -435,8 +435,8 @@ static HybridNonlinearFactorGraph createHybridNonlinearFactorGraph() {
       std::make_shared<BetweenFactor<double>>(X(0), X(1), 0, noise_model);
   const auto one_motion =
       std::make_shared<BetweenFactor<double>>(X(0), X(1), 1, noise_model);
-  std::vector<std::pair<NonlinearFactor::shared_ptr, double>> components = {
-      {zero_motion, 0.0}, {one_motion, 0.0}};
+  std::vector<NonlinearFactorValuePair> components = {{zero_motion, 0.0},
+                                                      {one_motion, 0.0}};
   nfg.emplace_shared<HybridNonlinearFactor>(KeyVector{X(0), X(1)},
                                             DiscreteKeys{m}, components);
 
@@ -595,8 +595,8 @@ TEST(HybridEstimation, ModeSelection) {
        model1 = std::make_shared<MotionModel>(
            X(0), X(1), 0.0, noiseModel::Isotropic::Sigma(d, noise_tight));
 
-  std::vector<std::pair<NonlinearFactor::shared_ptr, double>> components = {
-      {model0, 0.0}, {model1, 0.0}};
+  std::vector<NonlinearFactorValuePair> components = {{model0, 0.0},
+                                                      {model1, 0.0}};
 
   KeyVector keys = {X(0), X(1)};
   HybridNonlinearFactor mf(keys, modes, components);
@@ -687,8 +687,8 @@ TEST(HybridEstimation, ModeSelection2) {
        model1 = std::make_shared<BetweenFactor<Vector3>>(
            X(0), X(1), Z_3x1, noiseModel::Isotropic::Sigma(d, noise_tight));
 
-  std::vector<std::pair<NonlinearFactor::shared_ptr, double>> components = {
-      {model0, 0.0}, {model1, 0.0}};
+  std::vector<NonlinearFactorValuePair> components = {{model0, 0.0},
+                                                      {model1, 0.0}};
 
   KeyVector keys = {X(0), X(1)};
   HybridNonlinearFactor mf(keys, modes, components);
diff --git a/gtsam/hybrid/tests/testHybridNonlinearFactor.cpp b/gtsam/hybrid/tests/testHybridNonlinearFactor.cpp
index fa31fbe7d..a4c1b4cc7 100644
--- a/gtsam/hybrid/tests/testHybridNonlinearFactor.cpp
+++ b/gtsam/hybrid/tests/testHybridNonlinearFactor.cpp
@@ -58,8 +58,7 @@ TEST(HybridNonlinearFactor, Printing) {
       std::make_shared<BetweenFactor<double>>(X(1), X(2), between0, model);
   auto f1 =
       std::make_shared<BetweenFactor<double>>(X(1), X(2), between1, model);
-  std::vector<std::pair<NonlinearFactor::shared_ptr, double>> factors{
-      {f0, 0.0}, {f1, 0.0}};
+  std::vector<NonlinearFactorValuePair> factors{{f0, 0.0}, {f1, 0.0}};
 
   HybridNonlinearFactor mixtureFactor({X(1), X(2)}, {m1}, factors);
 
@@ -87,8 +86,7 @@ static HybridNonlinearFactor getHybridNonlinearFactor() {
       std::make_shared<BetweenFactor<double>>(X(1), X(2), between0, model);
   auto f1 =
       std::make_shared<BetweenFactor<double>>(X(1), X(2), between1, model);
-  std::vector<std::pair<NonlinearFactor::shared_ptr, double>> factors{
-      {f0, 0.0}, {f1, 0.0}};
+  std::vector<NonlinearFactorValuePair> factors{{f0, 0.0}, {f1, 0.0}};
 
   return HybridNonlinearFactor({X(1), X(2)}, {m1}, factors);
 }
diff --git a/gtsam/hybrid/tests/testHybridNonlinearFactorGraph.cpp b/gtsam/hybrid/tests/testHybridNonlinearFactorGraph.cpp
index 16098af7e..00d0d3a39 100644
--- a/gtsam/hybrid/tests/testHybridNonlinearFactorGraph.cpp
+++ b/gtsam/hybrid/tests/testHybridNonlinearFactorGraph.cpp
@@ -27,6 +27,7 @@
 #include <gtsam/hybrid/HybridNonlinearFactorGraph.h>
 #include <gtsam/linear/GaussianBayesNet.h>
 #include <gtsam/linear/GaussianFactorGraph.h>
+#include <gtsam/linear/NoiseModel.h>
 #include <gtsam/nonlinear/NonlinearFactorGraph.h>
 #include <gtsam/nonlinear/PriorFactor.h>
 #include <gtsam/sam/BearingRangeFactor.h>
@@ -867,7 +868,7 @@ static HybridNonlinearFactorGraph CreateFactorGraph(
       std::make_shared<BetweenFactor<double>>(X(0), X(1), means[1], model1);
 
   // Create HybridNonlinearFactor
-  std::vector<std::pair<NonlinearFactor::shared_ptr, double>> factors{
+  std::vector<NonlinearFactorValuePair> factors{
       {f0, ComputeLogNormalizer(model0)}, {f1, ComputeLogNormalizer(model1)}};
 
   HybridNonlinearFactor mixtureFactor({X(0), X(1)}, {m1}, factors);