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This is a proof without words of Jensen's inequality for n variables. Without loss of generality, the sum of the positive weights is 1. It follows that the weighted point lies in the convex hull of the original points, which lies above the function itself by the definition of convexity. The conclusion follows. [10]
This characterization of convexity is quite useful to prove the following results. A convex function of one real variable defined on some open interval is continuous on . admits left and right derivatives, and these are monotonically non-decreasing. In addition, the left derivative is left-continuous and the right-derivative is right-continuous.
Convexity is a geometric property with a variety of applications in economics. [1] Informally, an economic phenomenon is convex when "intermediates (or combinations) are better than extremes". For example, an economic agent with convex preferences prefers combinations of goods over having a lot of any one sort of good; this represents a kind of ...
Convexity in the first argument: by definition, and use convexity of F. Same for strict convexity. Linearity in F, law of cosines, parallelogram law: by definition. Duality: See figure 1 of. [4] Bregman balls are bounded, and compact if X is closed: Fix .
Let X be a convex subset of a real vector space, and let f : X → R be a function taking non-negative values. Then f is: . Logarithmically convex if is convex, and; Strictly logarithmically convex if is strictly convex.
In mathematics, the modulus of convexity and the characteristic of convexity are measures of "how convex" the unit ball in a Banach space is. In some sense, the modulus of convexity has the same relationship to the ε-δ definition of uniform convexity as the modulus of continuity does to the ε-δ definition of continuity.
For a function of a single variable, along any stretch of the curve the highest point is one of the endpoints. The negative of a quasiconvex function is said to be quasiconcave. Quasiconvexity is a more general property than convexity in that all convex functions are also quasiconvex, but not all quasiconvex functions are convex.
Proving a negative or negative proof may refer to: Proving a negative, in the philosophic burden of proof; Evidence of absence in general, such as evidence that there is no milk in a certain bowl; Modus tollens, a logical proof; Proof of impossibility, mathematics; Russell's teapot, an analogy: inability to disprove does not prove