diff --git a/examples/SFMExample_bal_COLAMD_METIS.cpp b/examples/SFMExample_bal_COLAMD_METIS.cpp
index 7d9457b9e..3ccdf9b72 100644
--- a/examples/SFMExample_bal_COLAMD_METIS.cpp
+++ b/examples/SFMExample_bal_COLAMD_METIS.cpp
@@ -80,8 +80,6 @@ int main (int argc, char* argv[]) {
   /** ---------------  COMPARISON  -----------------------**/
   /** ----------------------------------------------------**/
 
-  /** ---------------------------------------------------**/
-
   double t_COLAMD_ordering, t_METIS_ordering; //, t_NATURAL_ordering;
   LevenbergMarquardtParams params_using_COLAMD, params_using_METIS, params_using_NATURAL;
   try {
diff --git a/examples/SolverComparer.cpp b/examples/SolverComparer.cpp
index 923b0b9de..0f61a4220 100644
--- a/examples/SolverComparer.cpp
+++ b/examples/SolverComparer.cpp
@@ -589,7 +589,7 @@ void runStats()
 {
   cout << "Gathering statistics..." << endl;
   GaussianFactorGraph linear = *datasetMeasurements.linearize(initial);
-  GaussianJunctionTree jt(GaussianEliminationTree(linear, Ordering::colamd(linear)));
+  GaussianJunctionTree jt(GaussianEliminationTree(linear, Ordering::Colamd(linear)));
   treeTraversal::ForestStatistics statistics = treeTraversal::GatherStatistics(jt);
 
   ofstream file;
diff --git a/gtsam/inference/EliminateableFactorGraph-inst.h b/gtsam/inference/EliminateableFactorGraph-inst.h
index 5e261e200..b4fc3b3a6 100644
--- a/gtsam/inference/EliminateableFactorGraph-inst.h
+++ b/gtsam/inference/EliminateableFactorGraph-inst.h
@@ -55,9 +55,9 @@ namespace gtsam {
       // have a VariableIndex already here because we computed one if needed in the previous 'else'
       // block.
       if (orderingType == Ordering::METIS)
-	      return eliminateSequential(Ordering::metis(asDerived()), function, variableIndex, orderingType);
-	    else
-		    return eliminateSequential(Ordering::colamd(*variableIndex), function, variableIndex, orderingType);
+        return eliminateSequential(Ordering::Metis(asDerived()), function, variableIndex, orderingType);
+      else
+        return eliminateSequential(Ordering::Colamd(*variableIndex), function, variableIndex, orderingType);
     }
   }
 
@@ -93,9 +93,9 @@ namespace gtsam {
       // have a VariableIndex already here because we computed one if needed in the previous 'else'
       // block.
 	    if (orderingType == Ordering::METIS)
-		    return eliminateMultifrontal(Ordering::metis(asDerived()), function, variableIndex, orderingType);
+		    return eliminateMultifrontal(Ordering::Metis(asDerived()), function, variableIndex, orderingType);
 	    else
-		    return eliminateMultifrontal(Ordering::colamd(*variableIndex), function, variableIndex, orderingType);
+		    return eliminateMultifrontal(Ordering::Colamd(*variableIndex), function, variableIndex, orderingType);
     }
   }
 
@@ -125,7 +125,7 @@ namespace gtsam {
     if(variableIndex) {
       gttic(eliminatePartialSequential);
       // Compute full ordering
-      Ordering fullOrdering = Ordering::colamdConstrainedFirst(*variableIndex, variables);
+      Ordering fullOrdering = Ordering::ColamdConstrainedFirst(*variableIndex, variables);
 
       // Split off the part of the ordering for the variables being eliminated
       Ordering ordering(fullOrdering.begin(), fullOrdering.begin() + variables.size());
@@ -163,7 +163,7 @@ namespace gtsam {
     if(variableIndex) {
       gttic(eliminatePartialMultifrontal);
       // Compute full ordering
-      Ordering fullOrdering = Ordering::colamdConstrainedFirst(*variableIndex, variables);
+      Ordering fullOrdering = Ordering::ColamdConstrainedFirst(*variableIndex, variables);
 
       // Split off the part of the ordering for the variables being eliminated
       Ordering ordering(fullOrdering.begin(), fullOrdering.begin() + variables.size());
@@ -216,7 +216,7 @@ namespace gtsam {
           boost::get<const Ordering&>(&variables) : boost::get<const std::vector<Key>&>(&variables);
 
         Ordering totalOrdering =
-          Ordering::colamdConstrainedLast(*variableIndex, *variablesOrOrdering, unmarginalizedAreOrdered);
+          Ordering::ColamdConstrainedLast(*variableIndex, *variablesOrOrdering, unmarginalizedAreOrdered);
 
         // Split up ordering
         const size_t nVars = variablesOrOrdering->size();
@@ -275,7 +275,7 @@ namespace gtsam {
           boost::get<const Ordering&>(&variables) : boost::get<const std::vector<Key>&>(&variables);
 
         Ordering totalOrdering =
-          Ordering::colamdConstrainedLast(*variableIndex, *variablesOrOrdering, unmarginalizedAreOrdered);
+          Ordering::ColamdConstrainedLast(*variableIndex, *variablesOrOrdering, unmarginalizedAreOrdered);
 
         // Split up ordering
         const size_t nVars = variablesOrOrdering->size();
@@ -301,7 +301,7 @@ namespace gtsam {
     if(variableIndex)
     {
       // Compute a total ordering for all variables
-      Ordering totalOrdering = Ordering::colamdConstrainedLast(*variableIndex, variables);
+      Ordering totalOrdering = Ordering::ColamdConstrainedLast(*variableIndex, variables);
 
       // Split out the part for the marginalized variables
       Ordering marginalizationOrdering(totalOrdering.begin(), totalOrdering.end() - variables.size());
diff --git a/gtsam/inference/ISAM-inst.h b/gtsam/inference/ISAM-inst.h
index 7cb3d9817..aebd3325a 100644
--- a/gtsam/inference/ISAM-inst.h
+++ b/gtsam/inference/ISAM-inst.h
@@ -46,7 +46,7 @@ namespace gtsam {
     const VariableIndex varIndex(factors);
     const FastSet<Key> newFactorKeys = newFactors.keys();
     const Ordering constrainedOrdering =
-      Ordering::colamdConstrainedLast(varIndex, std::vector<Key>(newFactorKeys.begin(), newFactorKeys.end()));
+      Ordering::ColamdConstrainedLast(varIndex, std::vector<Key>(newFactorKeys.begin(), newFactorKeys.end()));
     Base bayesTree = *factors.eliminateMultifrontal(constrainedOrdering, function, varIndex);
     this->roots_.insert(this->roots_.end(), bayesTree.roots().begin(), bayesTree.roots().end());
     this->nodes_.insert(bayesTree.nodes().begin(), bayesTree.nodes().end());
diff --git a/gtsam/inference/Ordering.cpp b/gtsam/inference/Ordering.cpp
index 0882b87d1..9f4a81d05 100644
--- a/gtsam/inference/Ordering.cpp
+++ b/gtsam/inference/Ordering.cpp
@@ -38,14 +38,14 @@ FastMap<Key, size_t> Ordering::invert() const {
 }
 
 /* ************************************************************************* */
-Ordering Ordering::colamd(const VariableIndex& variableIndex) {
+Ordering Ordering::Colamd(const VariableIndex& variableIndex) {
   // Call constrained version with all groups set to zero
   vector<int> dummy_groups(variableIndex.size(), 0);
-  return Ordering::colamdConstrained(variableIndex, dummy_groups);
+  return Ordering::ColamdConstrained(variableIndex, dummy_groups);
 }
 
 /* ************************************************************************* */
-Ordering Ordering::colamdConstrained(const VariableIndex& variableIndex,
+Ordering Ordering::ColamdConstrained(const VariableIndex& variableIndex,
     std::vector<int>& cmember) {
   gttic(Ordering_COLAMDConstrained);
 
@@ -115,7 +115,7 @@ Ordering Ordering::colamdConstrained(const VariableIndex& variableIndex,
 }
 
 /* ************************************************************************* */
-Ordering Ordering::colamdConstrainedLast(const VariableIndex& variableIndex,
+Ordering Ordering::ColamdConstrainedLast(const VariableIndex& variableIndex,
     const std::vector<Key>& constrainLast, bool forceOrder) {
   gttic(Ordering_COLAMDConstrainedLast);
 
@@ -137,11 +137,11 @@ Ordering Ordering::colamdConstrainedLast(const VariableIndex& variableIndex,
       ++group;
   }
 
-  return Ordering::colamdConstrained(variableIndex, cmember);
+  return Ordering::ColamdConstrained(variableIndex, cmember);
 }
 
 /* ************************************************************************* */
-Ordering Ordering::colamdConstrainedFirst(const VariableIndex& variableIndex,
+Ordering Ordering::ColamdConstrainedFirst(const VariableIndex& variableIndex,
     const std::vector<Key>& constrainFirst, bool forceOrder) {
   gttic(Ordering_COLAMDConstrainedFirst);
 
@@ -170,11 +170,11 @@ Ordering Ordering::colamdConstrainedFirst(const VariableIndex& variableIndex,
     if (c == none)
       c = group;
 
-  return Ordering::colamdConstrained(variableIndex, cmember);
+  return Ordering::ColamdConstrained(variableIndex, cmember);
 }
 
 /* ************************************************************************* */
-Ordering Ordering::colamdConstrained(const VariableIndex& variableIndex,
+Ordering Ordering::ColamdConstrained(const VariableIndex& variableIndex,
     const FastMap<Key, int>& groups) {
   gttic(Ordering_COLAMDConstrained);
   size_t n = variableIndex.size();
@@ -193,11 +193,11 @@ Ordering Ordering::colamdConstrained(const VariableIndex& variableIndex,
     cmember[keyIndices.at(p.first)] = p.second;
   }
 
-  return Ordering::colamdConstrained(variableIndex, cmember);
+  return Ordering::ColamdConstrained(variableIndex, cmember);
 }
 
 /* ************************************************************************* */
-Ordering Ordering::metis(const MetisIndex& met) {
+Ordering Ordering::Metis(const MetisIndex& met) {
   gttic(Ordering_METIS);
 
   vector<idx_t> xadj = met.xadj();
diff --git a/gtsam/inference/Ordering.h b/gtsam/inference/Ordering.h
index 109fa1784..0ec5774e5 100644
--- a/gtsam/inference/Ordering.h
+++ b/gtsam/inference/Ordering.h
@@ -38,7 +38,7 @@ public:
 
   /// Type of ordering to use
   enum OrderingType {
-    COLAMD, METIS, CUSTOM, NATURAL
+    COLAMD, METIS, NATURAL, CUSTOM
   };
 
   typedef Ordering This; ///< Typedef to this class
@@ -78,12 +78,12 @@ public:
   /// performance). This internally builds a VariableIndex so if you already have a VariableIndex,
   /// it is faster to use COLAMD(const VariableIndex&)
   template<class FACTOR>
-  static Ordering colamd(const FactorGraph<FACTOR>& graph) {
-    return colamd(VariableIndex(graph));
+  static Ordering Colamd(const FactorGraph<FACTOR>& graph) {
+    return Colamd(VariableIndex(graph));
   }
 
   /// Compute a fill-reducing ordering using COLAMD from a VariableIndex.
-  static GTSAM_EXPORT Ordering colamd(const VariableIndex& variableIndex);
+  static GTSAM_EXPORT Ordering Colamd(const VariableIndex& variableIndex);
 
   /// Compute a fill-reducing ordering using constrained COLAMD from a factor graph (see details
   /// for note on performance).  This internally builds a VariableIndex so if you already have a
@@ -94,9 +94,9 @@ public:
   /// constrainLast.   If \c forceOrder is false, the variables in \c constrainLast will be
   /// ordered after all the others, but will be rearranged by CCOLAMD to reduce fill-in as well.
   template<class FACTOR>
-  static Ordering colamdConstrainedLast(const FactorGraph<FACTOR>& graph,
+  static Ordering ColamdConstrainedLast(const FactorGraph<FACTOR>& graph,
       const std::vector<Key>& constrainLast, bool forceOrder = false) {
-    return colamdConstrainedLast(VariableIndex(graph), constrainLast,
+    return ColamdConstrainedLast(VariableIndex(graph), constrainLast,
         forceOrder);
   }
 
@@ -106,7 +106,7 @@ public:
   /// variables in \c constrainLast will be ordered in the same order specified in the vector<Key>
   /// \c constrainLast.   If \c forceOrder is false, the variables in \c constrainLast will be
   /// ordered after all the others, but will be rearranged by CCOLAMD to reduce fill-in as well.
-  static GTSAM_EXPORT Ordering colamdConstrainedLast(
+  static GTSAM_EXPORT Ordering ColamdConstrainedLast(
       const VariableIndex& variableIndex, const std::vector<Key>& constrainLast,
       bool forceOrder = false);
 
@@ -119,9 +119,9 @@ public:
   /// constrainLast.   If \c forceOrder is false, the variables in \c constrainFirst will be
   /// ordered after all the others, but will be rearranged by CCOLAMD to reduce fill-in as well.
   template<class FACTOR>
-  static Ordering colamdConstrainedFirst(const FactorGraph<FACTOR>& graph,
+  static Ordering ColamdConstrainedFirst(const FactorGraph<FACTOR>& graph,
       const std::vector<Key>& constrainFirst, bool forceOrder = false) {
-    return colamdConstrainedFirst(VariableIndex(graph), constrainFirst,
+    return ColamdConstrainedFirst(VariableIndex(graph), constrainFirst,
         forceOrder);
   }
 
@@ -132,7 +132,7 @@ public:
   /// vector<Key> \c constrainFirst.   If \c forceOrder is false, the variables in \c
   /// constrainFirst will be ordered after all the others, but will be rearranged by CCOLAMD to
   /// reduce fill-in as well.
-  static GTSAM_EXPORT Ordering colamdConstrainedFirst(
+  static GTSAM_EXPORT Ordering ColamdConstrainedFirst(
       const VariableIndex& variableIndex,
       const std::vector<Key>& constrainFirst, bool forceOrder = false);
 
@@ -146,9 +146,9 @@ public:
   /// function simply fills the \c cmember argument to CCOLAMD with the supplied indices, see the
   /// CCOLAMD documentation for more information.
   template<class FACTOR>
-  static Ordering colamdConstrained(const FactorGraph<FACTOR>& graph,
+  static Ordering ColamdConstrained(const FactorGraph<FACTOR>& graph,
       const FastMap<Key, int>& groups) {
-    return colamdConstrained(VariableIndex(graph), groups);
+    return ColamdConstrained(VariableIndex(graph), groups);
   }
 
   /// Compute a fill-reducing ordering using constrained COLAMD from a VariableIndex.  In this
@@ -158,12 +158,12 @@ public:
   /// appear in \c groups in arbitrary order.  Any variables not present in \c groups will be
   /// assigned to group 0.  This function simply fills the \c cmember argument to CCOLAMD with the
   /// supplied indices, see the CCOLAMD documentation for more information.
-  static GTSAM_EXPORT Ordering colamdConstrained(
+  static GTSAM_EXPORT Ordering ColamdConstrained(
       const VariableIndex& variableIndex, const FastMap<Key, int>& groups);
 
   /// Return a natural Ordering. Typically used by iterative solvers
   template<class FACTOR>
-  static Ordering natural(const FactorGraph<FACTOR> &fg) {
+  static Ordering Natural(const FactorGraph<FACTOR> &fg) {
     FastSet<Key> src = fg.keys();
     std::vector<Key> keys(src.begin(), src.end());
     std::stable_sort(keys.begin(), keys.end());
@@ -176,11 +176,11 @@ public:
       std::vector<int>& adj, const FactorGraph<FACTOR>& graph);
 
   /// Compute an ordering determined by METIS from a VariableIndex
-  static GTSAM_EXPORT Ordering metis(const MetisIndex& met);
+  static GTSAM_EXPORT Ordering Metis(const MetisIndex& met);
 
   template<class FACTOR>
-  static Ordering metis(const FactorGraph<FACTOR>& graph) {
-    return metis(MetisIndex(graph));
+  static Ordering Metis(const FactorGraph<FACTOR>& graph) {
+    return Metis(MetisIndex(graph));
   }
 
   /// @}
@@ -193,11 +193,11 @@ public:
 
     switch (orderingType) {
     case COLAMD:
-      return colamd(graph);
+      return Colamd(graph);
     case METIS:
-      return metis(graph);
+      return Metis(graph);
     case NATURAL:
-      return natural(graph);
+      return Natural(graph);
     case CUSTOM:
       throw std::runtime_error(
           "Ordering::Create error: called with CUSTOM ordering type.");
@@ -222,7 +222,7 @@ public:
 
 private:
   /// Internal COLAMD function
-  static GTSAM_EXPORT Ordering colamdConstrained(
+  static GTSAM_EXPORT Ordering ColamdConstrained(
       const VariableIndex& variableIndex, std::vector<int>& cmember);
 
   /** Serialization function */
diff --git a/gtsam/inference/tests/testOrdering.cpp b/gtsam/inference/tests/testOrdering.cpp
index 8f2c417d3..d789da9b0 100644
--- a/gtsam/inference/tests/testOrdering.cpp
+++ b/gtsam/inference/tests/testOrdering.cpp
@@ -46,17 +46,17 @@ TEST(Ordering, constrained_ordering) {
   SymbolicFactorGraph sfg = example::symbolicChain();
 
   // unconstrained version
-  Ordering actUnconstrained = Ordering::colamd(sfg);
+  Ordering actUnconstrained = Ordering::Colamd(sfg);
   Ordering expUnconstrained = Ordering(list_of(0)(1)(2)(3)(4)(5));
   EXPECT(assert_equal(expUnconstrained, actUnconstrained));
 
   // constrained version - push one set to the end
-  Ordering actConstrained = Ordering::colamdConstrainedLast(sfg, list_of(2)(4));
+  Ordering actConstrained = Ordering::ColamdConstrainedLast(sfg, list_of(2)(4));
   Ordering expConstrained = Ordering(list_of(0)(1)(5)(3)(4)(2));
   EXPECT(assert_equal(expConstrained, actConstrained));
 
   // constrained version - push one set to the start
-  Ordering actConstrained2 = Ordering::colamdConstrainedFirst(sfg,
+  Ordering actConstrained2 = Ordering::ColamdConstrainedFirst(sfg,
       list_of(2)(4));
   Ordering expConstrained2 = Ordering(list_of(2)(4)(0)(1)(3)(5));
   EXPECT(assert_equal(expConstrained2, actConstrained2));
@@ -76,7 +76,7 @@ TEST(Ordering, grouped_constrained_ordering) {
   constraints[4] = 1;
   constraints[5] = 2;
 
-  Ordering actConstrained = Ordering::colamdConstrained(sfg, constraints);
+  Ordering actConstrained = Ordering::ColamdConstrained(sfg, constraints);
   Ordering expConstrained = list_of(0)(1)(3)(2)(4)(5);
   EXPECT(assert_equal(expConstrained, actConstrained));
 }
@@ -195,7 +195,7 @@ TEST(Ordering, csr_format_4) {
   EXPECT(adjExpected.size() == mi.adj().size());
   EXPECT(adjExpected == adjAcutal);
 
-  Ordering metOrder = Ordering::metis(sfg);
+  Ordering metOrder = Ordering::Metis(sfg);
 
   // Test different symbol types
   sfg.push_factor(Symbol('l', 1));
@@ -204,7 +204,7 @@ TEST(Ordering, csr_format_4) {
   sfg.push_factor(Symbol('x', 3), Symbol('l', 1));
   sfg.push_factor(Symbol('x', 4), Symbol('l', 1));
 
-  Ordering metOrder2 = Ordering::metis(sfg);
+  Ordering metOrder2 = Ordering::Metis(sfg);
 }
 
 /* ************************************************************************* */
@@ -226,7 +226,7 @@ TEST(Ordering, metis) {
   EXPECT(adjExpected.size() == mi.adj().size());
   EXPECT(adjExpected == mi.adj());
 
-  Ordering metis = Ordering::metis(sfg);
+  Ordering metis = Ordering::Metis(sfg);
 }
 
 /* ************************************************************************* */
diff --git a/gtsam/linear/IterativeSolver.cpp b/gtsam/linear/IterativeSolver.cpp
index 89486962b..ab3ccde13 100644
--- a/gtsam/linear/IterativeSolver.cpp
+++ b/gtsam/linear/IterativeSolver.cpp
@@ -86,7 +86,7 @@ KeyInfo::KeyInfo(const GaussianFactorGraph &fg, const Ordering &ordering)
 
 /****************************************************************************/
 KeyInfo::KeyInfo(const GaussianFactorGraph &fg)
-  : ordering_(Ordering::natural(fg)) {
+  : ordering_(Ordering::Natural(fg)) {
   initialize(fg);
 }
 
diff --git a/gtsam/linear/SubgraphPreconditioner.cpp b/gtsam/linear/SubgraphPreconditioner.cpp
index af4e9dd4f..f5ee4ddfc 100644
--- a/gtsam/linear/SubgraphPreconditioner.cpp
+++ b/gtsam/linear/SubgraphPreconditioner.cpp
@@ -366,7 +366,7 @@ std::vector<size_t> SubgraphBuilder::sample(const std::vector<double> &weights,
 Subgraph::shared_ptr SubgraphBuilder::operator() (const GaussianFactorGraph &gfg) const {
 
   const SubgraphBuilderParameters &p = parameters_;
-  const Ordering inverse_ordering = Ordering::natural(gfg);
+  const Ordering inverse_ordering = Ordering::Natural(gfg);
   const FastMap<Key, size_t> forward_ordering = inverse_ordering.invert();
   const size_t n = inverse_ordering.size(), t = n * p.complexity_ ;
 
diff --git a/gtsam/nonlinear/ISAM2.cpp b/gtsam/nonlinear/ISAM2.cpp
index 3b3d76285..97735b5d5 100644
--- a/gtsam/nonlinear/ISAM2.cpp
+++ b/gtsam/nonlinear/ISAM2.cpp
@@ -341,7 +341,7 @@ boost::shared_ptr<FastSet<Key> > ISAM2::recalculate(const FastSet<Key>& markedKe
     Ordering order;
     if(constrainKeys)
     {
-      order = Ordering::colamdConstrained(variableIndex_, *constrainKeys);
+      order = Ordering::ColamdConstrained(variableIndex_, *constrainKeys);
     }
     else
     {
@@ -351,11 +351,11 @@ boost::shared_ptr<FastSet<Key> > ISAM2::recalculate(const FastSet<Key>& markedKe
         FastMap<Key, int> constraintGroups;
         BOOST_FOREACH(Key var, observedKeys)
           constraintGroups[var] = 1;
-        order = Ordering::colamdConstrained(variableIndex_, constraintGroups);
+        order = Ordering::ColamdConstrained(variableIndex_, constraintGroups);
       }
       else
       {
-        order = Ordering::colamd(variableIndex_);
+        order = Ordering::Colamd(variableIndex_);
       }
     }
     gttoc(ordering);
@@ -481,7 +481,7 @@ boost::shared_ptr<FastSet<Key> > ISAM2::recalculate(const FastSet<Key>& markedKe
 
     // Generate ordering
     gttic(Ordering);
-    Ordering ordering = Ordering::colamdConstrained(affectedFactorsVarIndex, constraintGroups);
+    Ordering ordering = Ordering::ColamdConstrained(affectedFactorsVarIndex, constraintGroups);
     gttoc(Ordering);
 
     ISAM2BayesTree::shared_ptr bayesTree = ISAM2JunctionTree(GaussianEliminationTree(
diff --git a/gtsam/nonlinear/NonlinearFactorGraph.cpp b/gtsam/nonlinear/NonlinearFactorGraph.cpp
index 238d3bc56..99a58a989 100644
--- a/gtsam/nonlinear/NonlinearFactorGraph.cpp
+++ b/gtsam/nonlinear/NonlinearFactorGraph.cpp
@@ -282,13 +282,13 @@ FastSet<Key> NonlinearFactorGraph::keys() const {
 /* ************************************************************************* */
 Ordering NonlinearFactorGraph::orderingCOLAMD() const
 {
-  return Ordering::colamd(*this);
+  return Ordering::Colamd(*this);
 }
 
 /* ************************************************************************* */
 Ordering NonlinearFactorGraph::orderingCOLAMDConstrained(const FastMap<Key, int>& constraints) const
 {
-  return Ordering::colamdConstrained(*this, constraints);
+  return Ordering::ColamdConstrained(*this, constraints);
 }
 
 /* ************************************************************************* */
diff --git a/gtsam_unstable/nonlinear/BatchFixedLagSmoother.cpp b/gtsam_unstable/nonlinear/BatchFixedLagSmoother.cpp
index 05b0bb49e..952b134b5 100644
--- a/gtsam_unstable/nonlinear/BatchFixedLagSmoother.cpp
+++ b/gtsam_unstable/nonlinear/BatchFixedLagSmoother.cpp
@@ -191,7 +191,7 @@ void BatchFixedLagSmoother::reorder(const std::set<Key>& marginalizeKeys) {
   }
 
   // COLAMD groups will be used to place marginalize keys in Group 0, and everything else in Group 1
-  ordering_ = Ordering::colamdConstrainedFirst(factors_, std::vector<Key>(marginalizeKeys.begin(), marginalizeKeys.end()));
+  ordering_ = Ordering::ColamdConstrainedFirst(factors_, std::vector<Key>(marginalizeKeys.begin(), marginalizeKeys.end()));
 
   if(debug) {
     ordering_.print("New Ordering: ");
diff --git a/gtsam_unstable/nonlinear/ConcurrentBatchFilter.cpp b/gtsam_unstable/nonlinear/ConcurrentBatchFilter.cpp
index fcaae9626..40d1746ac 100644
--- a/gtsam_unstable/nonlinear/ConcurrentBatchFilter.cpp
+++ b/gtsam_unstable/nonlinear/ConcurrentBatchFilter.cpp
@@ -362,9 +362,9 @@ void ConcurrentBatchFilter::reorder(const boost::optional<FastList<Key> >& keysT
 
   // COLAMD groups will be used to place marginalize keys in Group 0, and everything else in Group 1
   if(keysToMove && keysToMove->size() > 0) {
-    ordering_ = Ordering::colamdConstrainedFirst(factors_, std::vector<Key>(keysToMove->begin(), keysToMove->end()));
+    ordering_ = Ordering::ColamdConstrainedFirst(factors_, std::vector<Key>(keysToMove->begin(), keysToMove->end()));
   }else{
-    ordering_ = Ordering::colamd(factors_);
+    ordering_ = Ordering::Colamd(factors_);
   }
 
 }
diff --git a/gtsam_unstable/nonlinear/ConcurrentBatchSmoother.cpp b/gtsam_unstable/nonlinear/ConcurrentBatchSmoother.cpp
index 0f6515056..c410ad528 100644
--- a/gtsam_unstable/nonlinear/ConcurrentBatchSmoother.cpp
+++ b/gtsam_unstable/nonlinear/ConcurrentBatchSmoother.cpp
@@ -231,7 +231,7 @@ void ConcurrentBatchSmoother::reorder() {
   variableIndex_ = VariableIndex(factors_);
 
   FastList<Key> separatorKeys = separatorValues_.keys();
-  ordering_ = Ordering::colamdConstrainedLast(variableIndex_, std::vector<Key>(separatorKeys.begin(), separatorKeys.end()));
+  ordering_ = Ordering::ColamdConstrainedLast(variableIndex_, std::vector<Key>(separatorKeys.begin(), separatorKeys.end()));
 
 }
 
diff --git a/tests/testNonlinearFactorGraph.cpp b/tests/testNonlinearFactorGraph.cpp
index f398a33fe..8e6b033e9 100644
--- a/tests/testNonlinearFactorGraph.cpp
+++ b/tests/testNonlinearFactorGraph.cpp
@@ -79,14 +79,14 @@ TEST( NonlinearFactorGraph, GET_ORDERING)
 {
   Ordering expected; expected += L(1), X(2), X(1); // For starting with l1,x1,x2
   NonlinearFactorGraph nlfg = createNonlinearFactorGraph();
-  Ordering actual = Ordering::colamd(nlfg);
+  Ordering actual = Ordering::Colamd(nlfg);
   EXPECT(assert_equal(expected,actual));
 
   // Constrained ordering - put x2 at the end
   Ordering expectedConstrained; expectedConstrained += L(1), X(1), X(2);
   FastMap<Key, int> constraints;
   constraints[X(2)] = 1;
-  Ordering actualConstrained = Ordering::colamdConstrained(nlfg, constraints);
+  Ordering actualConstrained = Ordering::ColamdConstrained(nlfg, constraints);
   EXPECT(assert_equal(expectedConstrained, actualConstrained));
 }