In mathematics, a concave function is the negative of a convex function. A concave function is also synonymously called concave downwards, concave down, convex upwards, convex cap or upper convex.
Contents

Definition 1

Properties 2

Examples 3

See also 4

Notes 5

References 6
Definition
A realvalued function f on an interval (or, more generally, a convex set in vector space) is said to be concave if, for any x and y in the interval and for any t in [0,1],

f((1t)x+(t)y)\geq (1t) f(x)+(t)f(y).
A function is called strictly concave if

f((1t)x + (t)y) > (1t) f(x) + (t)f(y)\,
for any t in (0,1) and x ≠ y.
For a function f:R→R, this definition merely states that for every z between x and y, the point (z, f(z) ) on the graph of f is above the straight line joining the points (x, f(x) ) and (y, f(y) ).
A function f(x) is quasiconcave if the upper contour sets of the function S(a)=\{x: f(x)\geq a\} are convex sets.
Properties
A function f(x) is concave over a convex set if and only if the function −f(x) is a convex function over the set.
A differentiable function f is concave on an interval if its derivative function f ′ is monotonically decreasing on that interval: a concave function has a decreasing slope. ("Decreasing" here means nonincreasing, rather than strictly decreasing, and thus allows zero slopes.)
For a twicedifferentiable function f, if the second derivative, f ′′(x), is positive (or, if the acceleration is positive), then the graph is convex; if f ′′(x) is negative, then the graph is concave. Points where concavity changes are inflection points.
If a convex (i.e., concave upward) function has a "bottom", any point at the bottom is a minimal extremum. If a concave (i.e., concave downward) function has an "apex", any point at the apex is a maximal extremum.
If f(x) is twicedifferentiable, then f(x) is concave if and only if f ′′(x) is nonpositive. If its second derivative is negative then it is strictly concave, but the opposite is not true, as shown by f(x) = x^{4}.
If f is concave and differentiable, then it is bounded above by its firstorder Taylor approximation:

f(y) \leq f(x) + f'(x)[yx]
A continuous function on C is concave if and only if for any x and y in C

f\left( \frac{x+y}2 \right) \ge \frac{f(x) + f(y)}2
If a function f is concave, and f(0) ≥ 0, then f is subadditive. Proof:

since f is concave, let y = 0, f(tx) = f(tx+(1t)\cdot 0) \ge t f(x)+(1t)f(0) \ge t f(x)

f(a) + f(b) = f \left((a+b) \frac{a}{a+b} \right) + f \left((a+b) \frac{b}{a+b} \right) \ge \frac{a}{a+b} f(a+b) + \frac{b}{a+b} f(a+b) = f(a+b)
Examples
See also
Notes
References

Crouzeix, J.P. (2008). "Quasiconcavity". In Durlauf, Steven N.; Blume, Lawrence E. The New Palgrave Dictionary of Economics (Second ed.). Palgrave Macmillan.

Rao, Singiresu S. (2009). Engineering Optimization: Theory and Practice. John Wiley and Sons. p. 779.

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