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The second derivative of a function f can be used to determine the concavity of the graph of f. [2] A function whose second derivative is positive is said to be concave up (also referred to as convex), meaning that the tangent line near the point where it touches the function will lie below the graph of the function.
A sufficient existence condition for a point of inflection in the case that f(x) is k times continuously differentiable in a certain neighborhood of a point x 0 with k odd and k ≥ 3, is that f (n) (x 0) = 0 for n = 2, ..., k − 1 and f (k) (x 0) ≠ 0. Then f(x) has a point of inflection at x 0. Another more general sufficient existence ...
printf is a C standard library function that formats text and writes it to standard output. The name, printf is short for print formatted where print refers to output to a printer although the functions are not limited to printer output. The standard library provides many other similar functions that form a family of printf-like functions.
In mathematics, the derivative is a fundamental tool that quantifies the sensitivity to change of a function's output with respect to its input. The derivative of a function of a single variable at a chosen input value, when it exists, is the slope of the tangent line to the graph of the function at that point.
Points where concavity changes (between concave and convex) are inflection points. [5] If f is twice-differentiable, then f is concave if and only if f ′′ is non-positive (or, informally, if the "acceleration" is non-positive). If f ′′ is negative then f is strictly concave, but the converse is not true, as shown by f(x) = −x 4.
Stated precisely, suppose that f is a real-valued function defined on some open interval containing the point x and suppose further that f is continuous at x. If there exists a positive number r > 0 such that f is weakly increasing on (x − r, x] and weakly decreasing on [x, x + r), then f has a local maximum at x.
However, the reverse does not necessarily hold. An example is the Gaussian function f(x) = exp(−x 2 /2) which is log-concave since log f(x) = −x 2 /2 is a concave function of x. But f is not concave since the second derivative is positive for | x | > 1: ″ = From above two points, concavity log-concavity quasiconcavity. A twice ...
In mathematics, concavification is the process of converting a non-concave function to a concave function. A related concept is convexification – converting a non-convex function to a convex function. It is especially important in economics and mathematical optimization. [1]