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

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 stoch...

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Bibliographic Details
Published inPhysical review. E, Statistical, nonlinear, and soft matter physics Vol. 72; no. 2 Pt 2; p. 026121
Main Authors Podobnik, Boris, Ivanov, Plamen Ch, Biljakovic, Katica, Horvatic, Davor, Stanley, H Eugene, Grosse, Ivo
Format Journal Article
LanguageEnglish
Published United States 01.08.2005
Subjects
Algorithms
Computer Simulation
Fourier Analysis
Heart - physiology
Heart Rate
Humans
Models, Biological
Models, Cardiovascular
Models, Statistical
Stochastic Processes
Temperature
Time Factors
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Summary: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.
ISSN:1539-3755
DOI:10.1103/PhysRevE.72.026121