Block sampling under strong dependence

STOCHASTIC PROCESSES AND THEIR APPLICATIONS

卷:123

Article

Zhang, Ting¹  Ho, Hwai-Chung²  Wendler, Martin³  Wu, Wei Biao⁴ 

[1] Univ Iowa, Dept Stat & Actuarial Sci, Iowa City, IA 52242 USA

[2] Acad Sinica, Inst Stat Sci, Taipei 115, Taiwan

[3] Ruhr Univ Bochum, Fak Math, Bochum, Germany

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

关键词: Asymptotic normality;    Covariance;    Hermite processes;    Linear processes;    Long-range dependence;    Rosenblatt distribution;   

DOI  :  10.1016/j.spa.2013.02.006

来源: Elsevier

【 摘 要 】

The paper considers the block sampling method for long-range dependent processes. Our theory generalizes earlier ones by Hall et al. (1998) [11] on functionals of Gaussian processes and Nordman and Lahiri (2005) [16] on linear processes. In particular, we allow nonlinear transforms of linear processes. Under suitable conditions on physical dependence measures, we prove the validity of the block sampling method. Its finite-sample performance is illustrated by a simulation study. (C) 2013 Elsevier B.V. All rights reserved.

【 授权许可】

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