Fractionally integrated process with power-law correlations in variables and magnitudes

Boris Podobnik, Plamen Ch. Ivanov, Katica Biljakovic, Davor Horvatic, H. Eugene Stanley, and Ivo Grosse
Phys. Rev. E 72, 026121 – Published 18 August 2005

Abstract

Motivated by the fact that many empirical time series—including changes of heartbeat intervals, physical activity levels, intertrade times in finance, and river flux values—exhibit power-law anticorrelations in the variables and power-law correlations in their magnitudes, we propose a simple stochastic process that can account for both types of correlations. The process depends on only two parameters, where one controls the correlations in the variables and the other controls the correlations in their magnitudes. We apply the process to time series of heartbeat interval changes and air temperature changes and find that the statistical properties of the modeled time series are in agreement with those observed in the data.

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  • Received 20 December 2004

DOI:https://doi.org/10.1103/PhysRevE.72.026121

©2005 American Physical Society

Authors & Affiliations

Boris Podobnik1,2,3, Plamen Ch. Ivanov2, Katica Biljakovic4, Davor Horvatic5, H. Eugene Stanley2, and Ivo Grosse3

  • 1Faculty of Civil Engineering, University of Rijeka, Rijeka, Croatia
  • 2Center for Polymer Studies and Department of Physics, Boston University, Boston, Massachusetts 02215, USA
  • 3Institute of Plant Genetics and Crop Plant Research (IPK), 06466 Gatersleben, Germany
  • 4Institute of Physics, Zagreb, Croatia
  • 5Department of Physics, Faculty of Science, University of Zagreb, Zagreb, Croatia

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Vol. 72, Iss. 2 — August 2005

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