arXiv · 1806.09062
A simplified and unified generalization of some majorization results
Abstract
We consider positive, integral-preserving linear operators acting on $L^1$ space, known as stochastic operators or Markov operators. We show that, on finite-dimensional spaces, any stochastic operator can be approximated by a sequence of stochastic integral operators (such operators arise naturally when considering matrix majorization in $L^1$). We collect a number of results for vector-valued functions on $L^1$, simplifying some proofs found in the literature. In particular, matrix majorization and multivariate majorization are related in $\mathbb{R}^n$. In $\mathbb{R}$, these are also equivalent to convex function inequalities.
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Shirin Moein, Rajesh Pereira, Sarah Plosker. 2018-06-24. A simplified and unified generalization of some majorization results. https://arxiv.org/abs/1806.09062
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