Moderate deviations for stationary processes

被引：0

作者：

Wu, Wei Biao ^{[1
]}

Zhao, Zhibiao ^{[2
]}

机构：

[1] Univ Chicago, Dept Stat, Chicago, IL 60637 USA

[2] Penn State Univ, Dept Stat, University Pk, PA 16802 USA

来源：

STATISTICA SINICA | 2008年 / 18卷 / 02期

关键词：

martingale; moderate deviation; nonlinear time series;

D O I：

暂无

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

We obtain asymptotic expansions for probabilities of moderate deviations for stationary causal processes. The imposed dependence conditions are easily verifiable and they are directly related to the data-generating mechanism of the underlying processes. The results are applied to functionals of linear processes and nonlinear time series. We carry out a simulation study and investigate the relationship between accuracy of tail probabilities and the strength of dependence.

引用

页码：769 / 782

页数：14

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