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Several Different Types of Convergence for ND Random Variables under Sublinear Expectations

机译:ublinear期望下的ND随机变量几种不同类型的收敛性

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The goal of this paper is to build average convergence and almost sure convergence for ND (negatively dependent) sequences of random variables under sublinear expectation space. By using the basic definition of sublinear expectation space, Markov inequality, and inequality, we extend average convergence and almost sure convergence theorems for ND sequences of random variables under sublinear expectation space, and we provide a way to learn this subject.
机译:本文的目标是建立平均收敛性,几乎肯定会在Sublinear期望空间下的随机变量的ND(负相关)序列的汇聚。 通过使用Sublinear期望空间的基本定义,Markov不等式和不平等,我们扩展了Sublinear期望空间下的随机变量ND序列的平均收敛性,并且我们提供了一种学习此主题的方法。

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