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

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

Physica A: Statistical Mechanics and its Applications, 2008, vol. 387, issue 15, 3954-3959

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.

Date: 2008
References: View complete reference list from CitEc
Citations: View citations in EconPapers (54)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:387:y:2008:i:15:p:3954-3959

DOI: 10.1016/j.physa.2008.01.062

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Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis

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