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arXiv 0810.0593math.PR
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信息不等式与一个相关的中心极限定理

Information inequalities and a dependent Central Limit Theorem

Oliver Johnson

摘要:

我们适应的中心极限定理的相关随机变量的情况下Rosenblatt混合条件下的信息理论收敛的参数。关键是要处理通过添加一个正常随机变量而扰动的随机变量,从而使我们能够很好地控制接头密度和混合系数。我们加强高野和Carlen和Soffer的结果,提供熵理论,而不是弱收敛。

英文摘要:

We adapt arguments concerning information-theoretic convergence in the Central Limit Theorem to the case of dependent random variables under Rosenblatt mixing conditions. The key is to work with random variables perturbed by the addition of a normal random variable, giving us good control of the joint density and the mixing coefficient. We strengthen results of Takano and of Carlen and Soffer to provide entropy-theoretic, not weak convergence.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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