In mathematics, a Schur-convex function, also known as S-convex, isotonic function and order-preserving function is a function that for all such that is majorized by , one has that . Named after Issai Schur, Schur-convex functions are used in the study of majorization. Every function that is convex and symmetric is also Schur-convex. The opposite implication is not true, but all Schur-convex functions are symmetric (under permutations of the arguments). Schur-concave function A function f is 'Schur-concave' if its negative, -f, is Schur-convex. Schur-Ostrowski criterion If f is symmetric and all first partial derivatives exist, then f is Schur-convex if and only if for all holds for all 1≤i≠j≤d. Examples is Schur-concave while is Schur-convex. This can be seen directly from the definition. The Shannon entropy function is Schur-concave. The Rényi entropy function is also Schur-concave. is Schur-convex. The function is Schur-concave, when we assume all . In the same way, all the Elementary symmetric functions are Schur-concave, when . A natural interpretation of majorization is that if then is less spread out than . So it is natural to ask if statistical measures of variability are Schur-convex. The variance and standard deviation are Schur-convex functions, while the Median absolute deviation is not. If is a convex function defined on a real interval, then is Schur-convex. A probability example: If are exchangeable random variables, then the function is Schur-convex as a function of , assuming that the expectations exist. The Gini coefficient is strictly Schur convex. References See also Quasiconvex function Convex analysis Inequalities