|  | @@ -324,10 +324,10 @@ steps:
 | 
	
		
			
				|  |  |      Rat43CostFunctor(const double x, const double y) : x_(x), y_(y) {}
 | 
	
		
			
				|  |  |  
 | 
	
		
			
				|  |  |      bool operator()(const double* parameters, double* residuals) const {
 | 
	
		
			
				|  |  | -      const double b1 = parameters[0][0];
 | 
	
		
			
				|  |  | -      const double b2 = parameters[0][1];
 | 
	
		
			
				|  |  | -      const double b3 = parameters[0][2];
 | 
	
		
			
				|  |  | -      const double b4 = parameters[0][3];
 | 
	
		
			
				|  |  | +      const double b1 = parameters[0];
 | 
	
		
			
				|  |  | +      const double b2 = parameters[1];
 | 
	
		
			
				|  |  | +      const double b3 = parameters[2];
 | 
	
		
			
				|  |  | +      const double b4 = parameters[3];
 | 
	
		
			
				|  |  |        residuals[0] = b1 * pow(1.0 + exp(b2 -  b3 * x_), -1.0 / b4) - y_;
 | 
	
		
			
				|  |  |        return true;
 | 
	
		
			
				|  |  |      }
 | 
	
	
		
			
				|  | @@ -686,10 +686,10 @@ implements an automatically differentiated ``CostFunction`` for
 | 
	
		
			
				|  |  |  
 | 
	
		
			
				|  |  |      template <typename T>
 | 
	
		
			
				|  |  |      bool operator()(const T* parameters, T* residuals) const {
 | 
	
		
			
				|  |  | -      const T b1 = parameters[0][0];
 | 
	
		
			
				|  |  | -      const T b2 = parameters[0][1];
 | 
	
		
			
				|  |  | -      const T b3 = parameters[0][2];
 | 
	
		
			
				|  |  | -      const T b4 = parameters[0][3];
 | 
	
		
			
				|  |  | +      const T b1 = parameters[0];
 | 
	
		
			
				|  |  | +      const T b2 = parameters[1];
 | 
	
		
			
				|  |  | +      const T b3 = parameters[2];
 | 
	
		
			
				|  |  | +      const T b4 = parameters[3];
 | 
	
		
			
				|  |  |        residuals[0] = b1 * pow(1.0 + exp(b2 -  b3 * x_), -1.0 / b4) - y_;
 | 
	
		
			
				|  |  |        return true;
 | 
	
		
			
				|  |  |      }
 | 
	
	
		
			
				|  | @@ -800,12 +800,12 @@ gives us the infinite series
 | 
	
		
			
				|  |  |  
 | 
	
		
			
				|  |  |  Here we are using the fact that :math:`\epsilon^2 = 0`.
 | 
	
		
			
				|  |  |  
 | 
	
		
			
				|  |  | -A **Jet** is a :math:`n`-dimensional dual number, where we augment the
 | 
	
		
			
				|  |  | -real numbers with :math:`n` infinitesimal units :math:`\epsilon_i,\
 | 
	
		
			
				|  |  | -i=1,...,n` with the property that :math:`\forall i, j\
 | 
	
		
			
				|  |  | -\epsilon_i\epsilon_j = 0`. Then a Jet consists of a *real* part
 | 
	
		
			
				|  |  | -:math:`a` and a :math:`n`-dimensional *infinitesimal* part
 | 
	
		
			
				|  |  | -:math:`\mathbf{v}`, i.e.,
 | 
	
		
			
				|  |  | +A `Jet <https://en.wikipedia.org/wiki/Jet_(mathematics)>`_ is a
 | 
	
		
			
				|  |  | +:math:`n`-dimensional dual number, where we augment the real numbers
 | 
	
		
			
				|  |  | +with :math:`n` infinitesimal units :math:`\epsilon_i,\ i=1,...,n` with
 | 
	
		
			
				|  |  | +the property that :math:`\forall i, j\ \epsilon_i\epsilon_j = 0`. Then
 | 
	
		
			
				|  |  | +a Jet consists of a *real* part :math:`a` and a :math:`n`-dimensional
 | 
	
		
			
				|  |  | +*infinitesimal* part :math:`\mathbf{v}`, i.e.,
 | 
	
		
			
				|  |  |  
 | 
	
		
			
				|  |  |  .. math::
 | 
	
		
			
				|  |  |     x = a + \sum_j v_{j} \epsilon_j
 | 
	
	
		
			
				|  | @@ -988,8 +988,6 @@ these points.
 | 
	
		
			
				|  |  |  	 constant times :math:`h^k` when :math:`h` is close enough to
 | 
	
		
			
				|  |  |  	 :math:`0`.
 | 
	
		
			
				|  |  |  
 | 
	
		
			
				|  |  | -
 | 
	
		
			
				|  |  | -
 | 
	
		
			
				|  |  |  TODO
 | 
	
		
			
				|  |  |  ====
 | 
	
		
			
				|  |  |  
 |