Convexity/Convex functions

A convex function f(x) is a real-valued function defined over a convex set X in a vector space such that for any two points x, y in the set and for any &lambda; with $$\displaystyle 0 \le \lambda \le 1,$$


 * $$\displaystyle f(\lambda x +(1-\lambda) y) \le \lambda f(x) + (1-\lambda) f(y).$$

NB: Because X is convex, :$$\displaystyle (\lambda x +(1-\lambda) y)$$ must be in X.

If the function -f(x) is convex, f(x) is said to ba a concave function. It is easily seen that if a function is both convex and concave, it must be linear.

Theorem: A convex function on X is bounded above on any compact subset of X.

Theorem: A convex function on X is continuous at each point of the interior of X.

Theorem: If f(x) is convex in a set containing the origin O, and f(O) = 0, then $f(&mu;x)/&mu;$ is an increasing function of &mu; for &mu; > 0.