Integrated approach to the assessment of long range correlation in time series data
Integrated approach to the assessment of long range correlation in time series data
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DOI：
10.1103/physreve.61.4991
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发表时间：
2000-05-01
影响因子：
2.4
通讯作者：
Ding, MZ
中科院分区：
文献类型：
--
作者：
Rangarajan, G;Ding, MZ
为了评估给定的时间序列是否可以用具有长程相关性的随机过程建模，人们通常使用两种分析方法之一：谱方法和随机游走分析。这项工作的第一个目标是证明，单独使用这些方法中的每一种都可能产生错误的结果。因此，我们主张采取一种综合办法，要求以一致的方式使用这两种方法。我们提供了这种方法的理论基础，并用例子说明了主要思想。第二个目标与观测长程反相关(赫斯特指数H)有关
To assess whether a given time series can be modeled by a stochastic process possessing long range correlation, one usually applies one of two types of analysis methods: the spectral method and the random walk analysis. The first objective of this work is to show that each one of these methods used alone can be susceptible to producing false results. We thus advocate an integrated approach which requires the use of both methods in a consistent fashion. We provide the theoretical foundation of this approach and illustrate the main ideas using examples. The second objective relates to the observation of long range anticorrelation (Hurst exponent H