BorderedHessian |
A bordered Hessian matrix consists of the Hessian of a multivariate function f,
and the gradient of a multivariate function g.
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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.
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GradientFunction |
The gradient function, g(x), evaluates the gradient of a real scalar function f at a point x.
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Hessian |
The Hessian matrix is the square matrix of the second-order partial derivatives of a multivariate function.
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HessianFunction |
The Hessian function, H(x), evaluates the Hessian of a real scalar function f at a point x.
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Jacobian |
The Jacobian matrix is the matrix of all first-order partial derivatives of a vector-valued function.
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JacobianFunction |
The Jacobian function, J(x), evaluates the Jacobian of a real vector-valued function f at a point x.
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MultivariateFiniteDifference |
A partial derivative of a multivariate function is the derivative with respect to one of the variables with the others held constant.
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