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BetaBit: A fast generator of autocorrelated binary processes for geophysical research
Publikationstyp
Journal Article
Date Issued
2017-05-01
Sprache
English
Author(s)
Serinaldi, Francesco
Journal
Volume
118
Issue
3
Article Number
30007
Citation
Epl 118 (3): 30007 (2017)
Publisher DOI
Scopus ID
Publisher
EDP Sciences
We introduce a fast and efficient non-iterative algorithm, called BetaBit, to simulate autocorrelated binary processes describing the occurrence of natural hazards, system failures, and other physical and geophysical phenomena characterized by persistence, temporal clustering, and low rate of occurrence. BetaBit overcomes the simulation constraints posed by the discrete nature of the marginal distributions of binary processes by using the link existing between the correlation coefficients of this process and those of the standard Gaussian processes. The performance of BetaBit is tested on binary signals with power-law and exponentially decaying autocorrelation functions (ACFs) corresponding to Hurst-Kolmogorov and Markov processes, respectively. An application to real-world sequences describing rainfall intermittency and the occurrence of strong positive phases of the North Atlantic Oscillation (NAO) index shows that BetaBit can also simulate surrogate data preserving the empirical ACF as well as signals with autoregressive moving average (ARMA) dependence structures. Extensions to cyclo-stationary processes accounting for seasonal fluctuations are also discussed.
DDC Class
600: Technology