diff --git a/gtsam/linear/NoiseModel.cpp b/gtsam/linear/NoiseModel.cpp
index 9cdb85c70..5a953eda5 100644
--- a/gtsam/linear/NoiseModel.cpp
+++ b/gtsam/linear/NoiseModel.cpp
@@ -552,7 +552,7 @@ Null::shared_ptr Null::Create()
 Fair::Fair(const double c, const ReweightScheme reweight)
   : Base(reweight), c_(c) {
   if ( c_ <= 0 ) {
-    cout << "MEstimator Fair takes only positive double in constructor. forced to 1.0" << endl;
+    cout << "mEstimator Fair takes only positive double in constructor. forced to 1.0" << endl;
     c_ = 1.0;
   }
 }
@@ -583,7 +583,7 @@ Fair::shared_ptr Fair::Create(const double c, const ReweightScheme reweight)
 Huber::Huber(const double k, const ReweightScheme reweight)
   : Base(reweight), k_(k) {
   if ( k_ <= 0 ) {
-    cout << "MEstimator Huber takes only positive double in constructor. forced to 1.0" << endl;
+    cout << "mEstimator Huber takes only positive double in constructor. forced to 1.0" << endl;
     k_ = 1.0;
   }
 }
@@ -636,7 +636,7 @@ Tukey::shared_ptr Tukey::Create(const double c, const ReweightScheme reweight) {
   return shared_ptr(new Tukey(c, reweight));
 }
 
-} // namespace MEstimator
+} // namespace mEstimator
 
 /* ************************************************************************* */
 // Robust
diff --git a/gtsam/linear/NoiseModel.h b/gtsam/linear/NoiseModel.h
index 73d9756a1..c36de4b10 100644
--- a/gtsam/linear/NoiseModel.h
+++ b/gtsam/linear/NoiseModel.h
@@ -571,7 +571,7 @@ namespace gtsam {
     };
 
     // TODO: should not really exist
-    /// The MEstimator namespace contains all robust error functions (not models)
+    /// The mEstimator namespace contains all robust error functions (not models)
     namespace mEstimator {
 
       //---------------------------------------------------------------------------------------
@@ -678,7 +678,7 @@ namespace gtsam {
         Tukey(){}
       };
 
-    } ///\namespace MEstimator
+    } ///\namespace mEstimator
 
     /// Base class for robust error models
     class Robust : public Base {
diff --git a/gtsam/linear/tests/testNoiseModel.cpp b/gtsam/linear/tests/testNoiseModel.cpp
index 9c40fca41..67023f591 100644
--- a/gtsam/linear/tests/testNoiseModel.cpp
+++ b/gtsam/linear/tests/testNoiseModel.cpp
@@ -294,7 +294,7 @@ TEST(NoiseModel, WhitenInPlace)
 TEST(NoiseModel, robustFunction)
 {
   const double k = 5.0, error1 = 1.0, error2 = 10.0;
-  const MEstimator::Huber::shared_ptr huber = MEstimator::Huber::Create(k);
+  const mEstimator::Huber::shared_ptr huber = mEstimator::Huber::Create(k);
   const double weight1 = huber->weight(error1),
                weight2 = huber->weight(error2);
   DOUBLES_EQUAL(1.0, weight1, 1e-8);
@@ -308,7 +308,7 @@ TEST(NoiseModel, robustNoise)
   Matrix A = Matrix_(2, 2, 1.0, 10.0, 100.0, 1000.0);
   Vector b = Vector_(2, error1, error2);
   const Robust::shared_ptr robust = Robust::Create(
-    MEstimator::Huber::Create(k, MEstimator::Huber::Scalar),
+    mEstimator::Huber::Create(k, mEstimator::Huber::Scalar),
     Unit::Create(2));
 
   robust->WhitenSystem(A,b);
diff --git a/tests/testNonlinearOptimizer.cpp b/tests/testNonlinearOptimizer.cpp
index 41221c7bc..aff07c15b 100644
--- a/tests/testNonlinearOptimizer.cpp
+++ b/tests/testNonlinearOptimizer.cpp
@@ -261,10 +261,10 @@ TEST(NonlinearOptimizer, MoreOptimizationWithHuber) {
   NonlinearFactorGraph fg;
   fg.add(PriorFactor<Pose2>(0, Pose2(0,0,0), noiseModel::Isotropic::Sigma(3,1)));
   fg.add(BetweenFactor<Pose2>(0, 1, Pose2(1,0,M_PI/2),
-                              noiseModel::Robust::Create(noiseModel::MEstimator::Huber::Create(2.0),
+                              noiseModel::Robust::Create(noiseModel::mEstimator::Huber::Create(2.0),
                                                          noiseModel::Isotropic::Sigma(3,1))));
   fg.add(BetweenFactor<Pose2>(1, 2, Pose2(1,0,M_PI/2),
-                              noiseModel::Robust::Create(noiseModel::MEstimator::Huber::Create(3.0),
+                              noiseModel::Robust::Create(noiseModel::mEstimator::Huber::Create(3.0),
                                                          noiseModel::Isotropic::Sigma(3,1))));
 
   Values init;