Integrated approach to the assessment of long range correlation in time series data

Rangarajan, Govindan ; Ding, Mingzhou (2000) Integrated approach to the assessment of long range correlation in time series data Physical Review E - Statistical, Nonlinear and Soft Matter Physics, 61 (5). pp. 4991-5001. ISSN 1539-3755

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Official URL: http://pre.aps.org/abstract/PRE/v61/i5/p4991_1

Related URL: http://dx.doi.org/10.1103/PhysRevE.61.4991

Abstract

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<½) in real world time series data. The very peculiar nature of such processes is emphasized in light of the stringent condition under which such processes can occur. Using examples, we discuss the possible factors that could contribute to the false claim of long range anticorrelations, and demonstrate the particular importance of the integrated approach in this case.

Item Type:Article
Source:Copyright of this article belongs to The American Physical Society.
ID Code:73208
Deposited On:02 Dec 2011 09:46
Last Modified:02 Dec 2011 09:46

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