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

Rangarajan, Govindan and Ding, Mingzhou (2000) Integrated approach to the assessment of long range correlation in time series data. In: Physical Review E, 61 (5). pp. 4991-5001.

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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<1/2) 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:	Journal Article
Publication:	Physical Review E
Publisher:	American Physical Society
Additional Information:	Copyright of this article belongs to American Physical Society.
Department/Centre:	Division of Physical & Mathematical Sciences > Centre for Theoretical Studies (Ceased to exist at the end of 2003) Division of Physical & Mathematical Sciences > Mathematics
Date Deposited:	28 Jul 2008
Last Modified:	19 Sep 2010 04:48
URI:	http://eprints.iisc.ac.in/id/eprint/15312

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