diff --git a/gtsam/nonlinear/LevenbergMarquardtOptimizer.cpp b/gtsam/nonlinear/LevenbergMarquardtOptimizer.cpp
index 6c4ff987b..b3a334a92 100644
--- a/gtsam/nonlinear/LevenbergMarquardtOptimizer.cpp
+++ b/gtsam/nonlinear/LevenbergMarquardtOptimizer.cpp
@@ -129,7 +129,7 @@ void LevenbergMarquardtOptimizer::iterate() {
            A.diagonal() = hessianDiagonal.at(key_value.key);
            for (size_t aa=0; aa<dim; aa++)
            {
-        	   A(aa,aa)=sqrt(std::min(std::max(A(aa,aa), min_diagonal_), max_diagonal_));
+        	   A(aa,aa)= sqrt(std::min(std::max(A(aa,aa), min_diagonal_), max_diagonal_));
            }
          }
         Vector b = Vector::Zero(dim);
diff --git a/tests/testNonlinearOptimizer.cpp b/tests/testNonlinearOptimizer.cpp
index cd3e354ee..a61f3912b 100644
--- a/tests/testNonlinearOptimizer.cpp
+++ b/tests/testNonlinearOptimizer.cpp
@@ -256,13 +256,14 @@ TEST(NonlinearOptimizer, MoreOptimization) {
   EXPECT(assert_equal(expected, DoglegOptimizer(fg, init).optimize()));
 
   // Try LM with diagonal damping
+  Values initBetter;
+  initBetter.insert(0, Pose2(3,4,0));
+  initBetter.insert(1, Pose2(10,2,M_PI/3));
+  initBetter.insert(2, Pose2(11,7,M_PI/2));
+
   LevenbergMarquardtParams params;
-  params.verbosityLM = gtsam::LevenbergMarquardtParams::DAMPED;
-  params.verbosity = gtsam::NonlinearOptimizerParams::ERROR;
   params.setDiagonalDamping(true);
-  params.setRelativeErrorTol(1e-9);
-  params.setAbsoluteErrorTol(1e-9);
-  LevenbergMarquardtOptimizer optimizer(fg, init, params);
+  LevenbergMarquardtOptimizer optimizer(fg, initBetter, params);
   EXPECT(assert_equal(expected, optimizer.optimize()));
 }