title: Fractionally integrated process with power-law correlations in variables and magnitudes.
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.
authors.affiliation: Faculty of Civil Engineering, University of Rijeka, Rijeka, Croatia.
authors.forename: Boris
authors.initials: B
authors.lastname: Podobnik
authors.forename: Plamen Ch
authors.initials: PCh
authors.lastname: Ivanov
authors.forename: Katica
authors.initials: K
authors.lastname: Biljakovic
authors.forename: Davor
authors.initials: D
authors.lastname: Horvatic
authors.forename: H Eugene
authors.initials: HE
authors.lastname: Stanley
authors.forename: Ivo
authors.initials: I
authors.lastname: Grosse
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D005583:Fourier Analysis; D006321:Heart / Q000502:physiology*; D006339:Heart Rate; D006801:Humans; D008954:Models, Biological; D008955:Models, Cardiovascular; D015233:Models, Statistical; D013269:Stochastic Processes; D013696:Temperature; D013997:Time Factors