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A capital H of second partial derivatives, testing whether a stationary point is a maximum or a minimum.
Also known as: Hessian, Hessian matrix, Second derivative matrix
The Hessian collects every second partial derivative into a square matrix, and its eigenvalues decide what kind of stationary point you are standing on. For a smooth function the matrix is symmetric, which is Clairaut's theorem doing quiet work.
Denotes the square matrix of second-order partial derivatives of a scalar function.
Contexts: Mathematics
Is symmetric wherever the second partial derivatives are continuous, so the order of differentiation does not matter — which halves the work of computing it.
Contexts: Mathematics
A capital letter H followed by a function name, standing for a bracketed square array of curled partial-derivative expressions.