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* The [[Rényi entropy]] function is also Schur-concave.
* <math> \sum_{i=1}^d{x_i^k},k \ge 1 </math> is Schur-convex.
* <math> \sum_{i=1}^d{x_i^k},0 < k < 1 </math> is Schur-concave.
* The function <math> f(x) = \prod_{i=1}^d x_i </math> is Schur-concave, when we assume all <math> x_i > 0 </math>. In the same way, all the [[Elementary symmetric polynomial|elementary symmetric function]]s are Schur-concave, when <math> x_i > 0 </math>.
* A natural interpretation of [[majorization]] is that if <math> x \succ y </math> then <math> x </math> is more spread out than <math> y </math>. 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.
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