Concave and Convex Functions

Definition

Let X be a subset of a vector space over R and f:XR be a function. f is called convex if and only if for all t(0,1) and x1,x2X,

f(tx1+(1t)x2)tf(x1)+(1t)f(x2).

Intuitively, this can be thought of (in the case where XR) as the line segment joining (x1,f(x1)) and (x2,f(x2)) being above the function.

A function is called concave if the above condition is changed with the reverse inequality:

f(tx1+(1t)x2)tf(x1)+(1t)f(x2).

The above conditions are called strict convexity and strict concavity respectively if the inequalities are strict. This is why we use the domain (0,1) for t rather than [0,1] even though the endpoints are trivially satisfied, so that these strict cases are meaningfully defined.


An important corollary of this result gives when the value f(a+b) can be compared to f(a)+f(b) described here.