Surrogate time series

被引:1323
作者
Schreiber, T [1 ]
Schmitz, A [1 ]
机构
[1] Univ Wuppertal, Dept Phys, D-42097 Wuppertal, Germany
关键词
time series; surrogate data; nonlinearity;
D O I
10.1016/S0167-2789(00)00043-9
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
Before we apply nonlinear techniques, e.g. those inspired by chaos theory, to dynamical phenomena occurring in nature, it is necessary to first ask if the use of such advanced techniques is justified by the data. While many processes in nature seem very unlikely a priori to be linear, the possible nonlinear nature might not be evident in specific aspects of their dynamics. The method of surrogate data has become a very popular tool to address such a question. However, while it was meant to provide a statistically rigorous, foolproof framework, some limitations and caveats have shown up in its practical use. In this paper, recent efforts to understand the caveats, avoid the pitfalls, and to overcome some of the limitations, are reviewed and augmented by new material. In particular, we will discuss specific as well as more general approaches to constrained randomisation, providing a full range of examples. New algorithms will be introduced for unevenly sampled and multivariate data and for surrogate spike trains. The main limitation, which lies in the interpretability of the test results, will be illustrated through instructive case studies. We will also discuss some implementational aspects of the realisation of these methods in the TISEAN software package. (C) 2000 Elsevier Science B.V. All rights reserved.
引用
收藏
页码:346 / 382
页数:37
相关论文
共 54 条
  • [51] Power of surrogate data testing with respect to nonstationarity
    Timmer, J
    [J]. PHYSICAL REVIEW E, 1998, 58 (04): : 5153 - 5156
  • [52] CHARACTERISTICS OF HAND TREMOR TIME-SERIES
    TIMMER, J
    GANTERT, C
    DEUSCHL, G
    HONERKAMP, J
    [J]. BIOLOGICAL CYBERNETICS, 1993, 70 (01) : 75 - 80
  • [53] *U CO BOULD NAT SN, 1997, GREENL SUMM IC COR C
  • [54] WEIGEND AS, 1993, TIME SERIES PREDICTI, V15