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Local and global maxima and minima for cos(3πx)/x, 0.1≤ x ≤1.1. In mathematical analysis, the maximum and minimum [a] of a function are, respectively, the greatest and least value taken by the function.
Perhaps the best-known example of the idea of locality lies in the concept of local minimum (or local maximum), which is a point in a function whose functional value is the smallest (resp., largest) within an immediate neighborhood of points. [1]
Fermat's theorem gives only a necessary condition for extreme function values, as some stationary points are inflection points (not a maximum or minimum). The function's second derivative, if it exists, can sometimes be used to determine whether a stationary point is a maximum or minimum.
After establishing the critical points of a function, the second-derivative test uses the value of the second derivative at those points to determine whether such points are a local maximum or a local minimum. [1] If the function f is twice-differentiable at a critical point x (i.e. a point where f ′ (x) = 0), then:
The Lagrange multiplier theorem states that at any local maximum (or minimum) of the function evaluated under the equality constraints, if constraint qualification applies (explained below), then the gradient of the function (at that point) can be expressed as a linear combination of the gradients of the constraints (at that point), with the ...
a local maximum (maximal turning point or relative maximum) is one where the derivative of the function changes from positive to negative; Saddle points (stationary points that are neither local maxima nor minima: they are inflection points. The left is a "rising point of inflection" (derivative is positive on both sides of the red point); the ...
The value of the function at a critical point is a critical value. [1] ... In this case, a non-degenerate critical point is a local maximum or a local minimum ...
A sufficient condition for a local maximum is that these minors alternate in sign with the smallest one having the sign of () +. A sufficient condition for a local minimum is that all of these minors have the sign of (). (In the unconstrained case of = these conditions coincide with the conditions for the unbordered Hessian to be negative ...