| Class | Description |
|---|---|
| BorderedHessian |
A bordered Hessian matrix consists of the Hessian of a multivariate function f,
and the gradient of a multivariate function g.
|
| FiniteDifference |
A partial derivative of a multivariate function is the derivative with respect to one of the variables with the others held constant.
|
| Gradient |
The gradient of a scalar field is a vector field which points in the direction of the greatest rate of increase of the scalar field,
and of which the magnitude is the greatest rate of change.
|
| GradientFunction |
The gradient function, g(x), evaluates the gradient of a real scalar function f at a point x.
|
| Hessian |
The Hessian matrix is the square matrix of the second-order partial derivatives of a multivariate function.
|
| HessianFunction |
The Hessian function, H(x), evaluates the Hessian of a real scalar function f at a point x.
|
| Jacobian |
The Jacobian matrix is the matrix of all first-order partial derivatives of a vector-valued function.
|
| JacobianFunction |
The Jacobian function, J(x), evaluates the Jacobian of a real vector-valued function f at a point x.
|