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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.
In calculus, a derivative test uses the derivatives of a function to locate the critical points of a function and determine whether each point is a local maximum, a local minimum, or a saddle point. Derivative tests can also give information about the concavity of a function. The usefulness of derivatives to find extrema is proved ...
Fermat used adequality first to find maxima of functions, and then adapted it to find tangent lines to curves. To find the maximum of a term p ( x ) {\displaystyle p(x)} , Fermat equated (or more precisely adequated) p ( x ) {\displaystyle p(x)} and p ( x + e ) {\displaystyle p(x+e)} and after doing algebra he could cancel out a factor of e ...
Thus in a totally ordered set, we can simply use the terms minimum and maximum. If a chain is finite, then it will always have a maximum and a minimum. If a chain is infinite, then it need not have a maximum or a minimum. For example, the set of natural numbers has no maximum, though it has a minimum.
Thus, the second partial derivative test indicates that f(x, y) has saddle points at (0, −1) and (1, −1) and has a local maximum at (,) since = <. At the remaining critical point (0, 0) the second derivative test is insufficient, and one must use higher order tests or other tools to determine the behavior of the function at this point.
if it is zero, then x could be a local minimum, a local maximum, or neither. (For example, f(x) = x 3 has a critical point at x = 0, but it has neither a maximum nor a minimum there, whereas f(x) = ± x 4 has a critical point at x = 0 and a minimum and a maximum, respectively, there.) This is called the second derivative test.
Newton's method uses curvature information (i.e. the second derivative) to take a more direct route. In calculus, Newton's method (also called Newton–Raphson) is an iterative method for finding the roots of a differentiable function, which are solutions to the equation =.
This is the definition of the derivative. All differentiation rules can also be reframed as rules involving limits. For example, if g(x) is differentiable at x, (+) = ′ [()] ′ (). This is the chain rule.