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The uniform CLT for martingale difference arrays under the uniformly integrable entropy

机译:一致可积熵下mar差阵列的一致CLT

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In this paper we consider the uniform central limit theorem for a martingale-difference array of a function-indexed stochastic process under the uniformly integrable entropy condition. We prove a maximal inequality for martingale-difference arrays of process indexed by a class of measurable functions by a method as Ziegler [19] did for triangular arrays of row wise independent process. The main tools are the Freedman inequality for the martingale-difference and a sub-Gaussian inequality based on the restricted chaining. The results of present paper generalizes those of Ziegler [19] and other results of independent problems. The results also generalizes those of Bae and Choi [3] to martingale-difference array of a function-indexed stochastic process. Finally, an application to classes of functions changing with $n$ is given.
机译:在本文中,我们考虑了在均匀可积分熵条件下函数索引随机过程的mar差分数组的统一中心极限定理。我们用Ziegler [19]对行独立过程的三角形数组所做的方法证明了由一类可测量函数索引的过程的mar差数组的最大不等式。主要工具是for差的Freedman不等式和基于受限链的次高斯不等式。本文的结果概括了Ziegler [19]以及其他独立问题的结果。结果也将Bae和Choi [3]的研究推广到功能指数随机过程的mar差矩阵。最后,给出了应用程序函数类随$ n $的变化。

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