diff --git a/tests/testPreconditioner.cpp b/tests/testPreconditioner.cpp
index bcb59afe7..7175059b9 100644
--- a/tests/testPreconditioner.cpp
+++ b/tests/testPreconditioner.cpp
@@ -34,11 +34,11 @@ static GaussianFactorGraph createSimpleGaussianFactorGraph() {
   // linearized prior on x1: c[_x1_]+x1=0 i.e. x1=-c[_x1_]
   fg += JacobianFactor(2, 10*eye(2), -1.0*ones(2), unit2);
   // odometry between x1 and x2: x2-x1=[0.2;-0.1]
-  fg += JacobianFactor(2, -10*eye(2), 0, 10*eye(2), (Vector(2) << 2.0, -1.0), unit2);
+  fg += JacobianFactor(2, -10*eye(2), 0, 10*eye(2), (Vector(2) << 2.0, -1.0).finished(), unit2);
   // measurement between x1 and l1: l1-x1=[0.0;0.2]
-  fg += JacobianFactor(2, -5*eye(2), 1, 5*eye(2), (Vector(2) << 0.0, 1.0), unit2);
+  fg += JacobianFactor(2, -5*eye(2), 1, 5*eye(2), (Vector(2) << 0.0, 1.0).finished(), unit2);
   // measurement between x2 and l1: l1-x2=[-0.2;0.3]
-  fg += JacobianFactor(0, -5*eye(2), 1, 5*eye(2), (Vector(2) << -1.0, 1.5), unit2);
+  fg += JacobianFactor(0, -5*eye(2), 1, 5*eye(2), (Vector(2) << -1.0, 1.5).finished(), unit2);
   return fg;
 }
 
@@ -49,11 +49,11 @@ static GaussianFactorGraph createSimpleGaussianFactorGraphUnordered() {
   // linearized prior on x1: c[_x1_]+x1=0 i.e. x1=-c[_x1_
   fg += JacobianFactor(2, 10*eye(2), -1.0*ones(2), unit2);
   // odometry between x1 and x2: x2-x1=[0.2;-0.1]
-  fg += JacobianFactor(2, -10*eye(2), 1, 10*eye(2), (Vector(2) << 2.0, -1.0), unit2);
+  fg += JacobianFactor(2, -10*eye(2), 1, 10*eye(2), (Vector(2) << 2.0, -1.0).finished(), unit2);
   // measurement between x1 and l1: l1-x1=[0.0;0.2]
-  fg += JacobianFactor(2, -5*eye(2), 1, 5*eye(2), (Vector(2) << 0.0, 1.0), unit2);
+  fg += JacobianFactor(2, -5*eye(2), 1, 5*eye(2), (Vector(2) << 0.0, 1.0).finished(), unit2);
   // measurement between x2 and l1: l1-x2=[-0.2;0.3]
-  fg += JacobianFactor(0, -5*eye(2), 1, 5*eye(2), (Vector(2) << -1.0, 1.5), unit2);
+  fg += JacobianFactor(0, -5*eye(2), 1, 5*eye(2), (Vector(2) << -1.0, 1.5).finished(), unit2);
   return fg;
 }
 
@@ -153,7 +153,7 @@ TEST( BlockJacobiPreconditioner, verySimpleLinerSystem) {
 
   // Create a Gaussian Factor Graph
   GaussianFactorGraph simpleGFG;
-  simpleGFG += JacobianFactor(0, (Matrix(2,2)<< 4, 1, 1, 3), (Vector(2) << 1,2 ), noiseModel::Unit::Create(2));
+  simpleGFG += JacobianFactor(0, (Matrix(2,2)<< 4, 1, 1, 3).finished(), (Vector(2) << 1, 2).finished(), noiseModel::Unit::Create(2));
   //simpleGFG.print("Factors\n");
 
   // Expected Hessian block diagonal matrices
@@ -176,7 +176,7 @@ TEST( BlockJacobiPreconditioner, verySimpleLinerSystem) {
   //
   Matrix expectedH0 = it1->second;
   Matrix actualH0 = *it2;
-  EXPECT(assert_equal(expectedH0, (Matrix(2,2) << 17, 7, 7, 10) ));
+  EXPECT(assert_equal(expectedH0, (Matrix(2,2) << 17, 7, 7, 10).finished() ));
   EXPECT(assert_equal(expectedH0, actualH0));
 
   // The corresponding Cholesky decomposition is:
@@ -184,7 +184,7 @@ TEST( BlockJacobiPreconditioner, verySimpleLinerSystem) {
   Preconditioner::shared_ptr preconditioner = createPreconditioner(boost::make_shared<gtsam::BlockJacobiPreconditionerParameters>());
   preconditioner->build(simpleGFG, KeyInfo(simpleGFG), std::map<Key,Vector>());
   boost::shared_ptr<BlockJacobiPreconditioner> blockJacobi = boost::dynamic_pointer_cast<BlockJacobiPreconditioner>(preconditioner);
-  Vector expectedR = (Vector(4) << 4.1231, 0, 1.6977, 2.6679);
+  Vector expectedR = (Vector(4) << 4.1231, 0, 1.6977, 2.6679).finished();
   double* buf = blockJacobi->getBuffer();
   for(int i=0; i<4; ++i){
 	  EXPECT_DOUBLES_EQUAL(expectedR(i), buf[i], 1e-4);
@@ -197,13 +197,13 @@ TEST( BlockJacobiPreconditioner, SimpleLinerSystem) {
   // Create a Gaussian Factor Graph
   GaussianFactorGraph simpleGFG;
   SharedDiagonal unit2 = noiseModel::Unit::Create(2);
-  simpleGFG += JacobianFactor(2, (Matrix(2,2)<< 10, 0, 0, 10), (Vector(2) << -1, -1), unit2);
-  simpleGFG += JacobianFactor(2, (Matrix(2,2)<< -10, 0, 0, -10), 0, (Matrix(2,2)<< 10, 0, 0, 10), (Vector(2) << 2, -1), unit2);
-  simpleGFG += JacobianFactor(2, (Matrix(2,2)<< -5, 0, 0, -5), 1, (Matrix(2,2)<< 5, 0, 0, 5), (Vector(2) << 0, 1), unit2);
-  simpleGFG += JacobianFactor(0, (Matrix(2,2)<< -5, 0, 0, -5), 1, (Matrix(2,2)<< 5, 0, 0, 5), (Vector(2) << -1, 1.5), unit2);
-  simpleGFG += JacobianFactor(0, (Matrix(2,2)<< 1, 0, 0, 1), (Vector(2) << 0, 0), unit2);
-  simpleGFG += JacobianFactor(1, (Matrix(2,2)<< 1, 0, 0, 1), (Vector(2) << 0, 0), unit2);
-  simpleGFG += JacobianFactor(2, (Matrix(2,2)<< 1, 0, 0, 1), (Vector(2) << 0, 0), unit2);
+  simpleGFG += JacobianFactor(2, (Matrix(2,2)<< 10, 0, 0, 10).finished(), (Vector(2) << -1, -1).finished(), unit2);
+  simpleGFG += JacobianFactor(2, (Matrix(2,2)<< -10, 0, 0, -10).finished(), 0, (Matrix(2,2)<< 10, 0, 0, 10).finished(), (Vector(2) << 2, -1).finished(), unit2);
+  simpleGFG += JacobianFactor(2, (Matrix(2,2)<< -5, 0, 0, -5).finished(), 1, (Matrix(2,2)<< 5, 0, 0, 5).finished(), (Vector(2) << 0, 1).finished(), unit2);
+  simpleGFG += JacobianFactor(0, (Matrix(2,2)<< -5, 0, 0, -5).finished(), 1, (Matrix(2,2)<< 5, 0, 0, 5).finished(), (Vector(2) << -1, 1.5).finished(), unit2);
+  simpleGFG += JacobianFactor(0, (Matrix(2,2)<< 1, 0, 0, 1).finished(), (Vector(2) << 0, 0).finished(), unit2);
+  simpleGFG += JacobianFactor(1, (Matrix(2,2)<< 1, 0, 0, 1).finished(), (Vector(2) << 0, 0).finished(), unit2);
+  simpleGFG += JacobianFactor(2, (Matrix(2,2)<< 1, 0, 0, 1).finished(), (Vector(2) << 0, 0).finished(), unit2);
 
   // Expected Hessian block diagonal matrices
   std::map<Key, Matrix> expectedHessian =simpleGFG.hessianBlockDiagonal();
@@ -238,12 +238,12 @@ TEST( PCGsolver, verySimpleLinearSystem) {
 
   // Create a Gaussian Factor Graph
   GaussianFactorGraph simpleGFG;
-  simpleGFG += JacobianFactor(0, (Matrix(2,2)<< 4, 1, 1, 3), (Vector(2) << 1,2 ), noiseModel::Unit::Create(2));
+  simpleGFG += JacobianFactor(0, (Matrix(2,2)<< 4, 1, 1, 3).finished(), (Vector(2) << 1,2 ).finished(), noiseModel::Unit::Create(2));
   //simpleGFG.print("Factors\n");
 
   // Exact solution already known
   VectorValues exactSolution;
-  exactSolution.insert(0, (Vector(2) << 1./11., 7./11.));
+  exactSolution.insert(0, (Vector(2) << 1./11., 7./11.).finished());
   //exactSolution.print("Exact");
 
   // Solve the system using direct method
@@ -280,20 +280,20 @@ TEST(PCGSolver, simpleLinearSystem) {
   // Create a Gaussian Factor Graph
   GaussianFactorGraph simpleGFG;
   SharedDiagonal unit2 = noiseModel::Unit::Create(2);
-  simpleGFG += JacobianFactor(2, (Matrix(2,2)<< 10, 0, 0, 10), (Vector(2) << -1, -1), unit2);
-  simpleGFG += JacobianFactor(2, (Matrix(2,2)<< -10, 0, 0, -10), 0, (Matrix(2,2)<< 10, 0, 0, 10), (Vector(2) << 2, -1), unit2);
-  simpleGFG += JacobianFactor(2, (Matrix(2,2)<< -5, 0, 0, -5), 1, (Matrix(2,2)<< 5, 0, 0, 5), (Vector(2) << 0, 1), unit2);
-  simpleGFG += JacobianFactor(0, (Matrix(2,2)<< -5, 0, 0, -5), 1, (Matrix(2,2)<< 5, 0, 0, 5), (Vector(2) << -1, 1.5), unit2);
-  simpleGFG += JacobianFactor(0, (Matrix(2,2)<< 1, 0, 0, 1), (Vector(2) << 0, 0), unit2);
-  simpleGFG += JacobianFactor(1, (Matrix(2,2)<< 1, 0, 0, 1), (Vector(2) << 0, 0), unit2);
-  simpleGFG += JacobianFactor(2, (Matrix(2,2)<< 1, 0, 0, 1), (Vector(2) << 0, 0), unit2);
+  simpleGFG += JacobianFactor(2, (Matrix(2,2)<< 10, 0, 0, 10).finished(), (Vector(2) << -1, -1).finished(), unit2);
+  simpleGFG += JacobianFactor(2, (Matrix(2,2)<< -10, 0, 0, -10).finished(), 0, (Matrix(2,2)<< 10, 0, 0, 10).finished(), (Vector(2) << 2, -1).finished(), unit2);
+  simpleGFG += JacobianFactor(2, (Matrix(2,2)<< -5, 0, 0, -5).finished(), 1, (Matrix(2,2)<< 5, 0, 0, 5).finished(), (Vector(2) << 0, 1).finished(), unit2);
+  simpleGFG += JacobianFactor(0, (Matrix(2,2)<< -5, 0, 0, -5).finished(), 1, (Matrix(2,2)<< 5, 0, 0, 5).finished(), (Vector(2) << -1, 1.5).finished(), unit2);
+  simpleGFG += JacobianFactor(0, (Matrix(2,2)<< 1, 0, 0, 1).finished(), (Vector(2) << 0, 0).finished(), unit2);
+  simpleGFG += JacobianFactor(1, (Matrix(2,2)<< 1, 0, 0, 1).finished(), (Vector(2) << 0, 0).finished(), unit2);
+  simpleGFG += JacobianFactor(2, (Matrix(2,2)<< 1, 0, 0, 1).finished(), (Vector(2) << 0, 0).finished(), unit2);
   //simpleGFG.print("Factors\n");
 
   // Expected solution
   VectorValues expectedSolution;
-  expectedSolution.insert(0, (Vector(2) << 0.100498, -0.196756));
-  expectedSolution.insert(2, (Vector(2) << -0.0990413, -0.0980577));
-  expectedSolution.insert(1, (Vector(2) << -0.0973252, 0.100582));
+  expectedSolution.insert(0, (Vector(2) << 0.100498, -0.196756).finished());
+  expectedSolution.insert(2, (Vector(2) << -0.0990413, -0.0980577).finished());
+  expectedSolution.insert(1, (Vector(2) << -0.0973252, 0.100582).finished());
 
   // Solve the system using direct method
   VectorValues deltaDirect = simpleGFG.optimize();
@@ -303,9 +303,9 @@ TEST(PCGSolver, simpleLinearSystem) {
 
   // Solve the system using PCG
   VectorValues initial;
-  initial.insert(0, (Vector(2) << 0.1, -0.1));
-  initial.insert(1, (Vector(2) << -0.1, 0.1));
-  initial.insert(2, (Vector(2) << -0.1, -0.1));
+  initial.insert(0, (Vector(2) << 0.1, -0.1).finished());
+  initial.insert(1, (Vector(2) << -0.1, 0.1).finished());
+  initial.insert(2, (Vector(2) << -0.1, -0.1).finished());
 
   // With Dummy preconditioner
   gtsam::PCGSolverParameters::shared_ptr pcg = boost::make_shared<gtsam::PCGSolverParameters>();