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Modeling long-range cross-correlations in two-component ARFIMA and FIARCH processes

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  • Podobnik, Boris
  • Horvatic, Davor
  • Lam Ng, Alfonso
  • Eugene Stanley, H.
  • Ivanov, Plamen Ch.

Abstract

We investigate how simultaneously recorded long-range power-law correlated multivariate signals cross-correlate. To this end we introduce a two-component ARFIMA stochastic process and a two-component FIARCH process to generate coupled fractal signals with long-range power-law correlations which are at the same time long-range cross-correlated. We study how the degree of cross-correlations between these signals depends on the scaling exponents characterizing the fractal correlations in each signal and on the coupling between the signals. Our findings have relevance when studying parallel outputs of multiple component of physical, physiological and social systems.

Suggested Citation

  • Podobnik, Boris & Horvatic, Davor & Lam Ng, Alfonso & Eugene Stanley, H. & Ivanov, Plamen Ch., 2008. "Modeling long-range cross-correlations in two-component ARFIMA and FIARCH processes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(15), pages 3954-3959.
  • Handle: RePEc:eee:phsmap:v:387:y:2008:i:15:p:3954-3959
    DOI: 10.1016/j.physa.2008.01.062
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