Revisiting Algorithms for Generating Surrogate Time Series

被引：21

作者：

Raeth, C. ^{[1
]}

Gliozzi, M. ^{[2
]}

Papadakis, I. E. ^{[3
,4
]}

Brinkmann, W. ^{[1
]}

机构：

[1] Max Planck Inst Extraterr Phys, D-85748 Garching, Germany

[2] George Mason Univ, Dept Phys & Astron, Fairfax, VA 22030 USA

[3] Univ Crete, Dept Phys, Iraklion 71003, Crete, Greece

[4] Fdn Res & Technol Hellas, IESL, Iraklion 71110, Crete, Greece

来源：

PHYSICAL REVIEW LETTERS | 2012年 / 109卷 / 14期

关键词：

NONLINEARITY;

D O I：

10.1103/PhysRevLett.109.144101

中图分类号：

O4 [物理学];

学科分类号：

0702 ;

摘要：

The method of surrogates is one of the key concepts of nonlinear data analysis. Here, we demonstrate that commonly used algorithms for generating surrogates often fail to generate truly linear time series. Rather, they create surrogate realizations with Fourier phase correlations leading to nondetections of nonlinearities. We argue that reliable surrogates can only be generated, if one tests separately for static and dynamic nonlinearities.

引用

页数：5

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