Options
General simulation algorithm for autocorrelated binary processes
Publikationstyp
Journal Article
Date Issued
2017-02-23
Sprache
English
Author(s)
Serinaldi, Francesco
Volume
95
Issue
2
Article Number
023312
Citation
Physical Review E 95 (2): 023312 (2017)
Publisher DOI
Scopus ID
Publisher
American Physical Society
The apparent ubiquity of binary random processes in physics and many other fields has attracted considerable attention from the modeling community. However, generation of binary sequences with prescribed autocorrelation is a challenging task owing to the discrete nature of the marginal distributions, which makes the application of classical spectral techniques problematic. We show that such methods can effectively be used if we focus on the parent continuous process of beta distributed transition probabilities rather than on the target binary process. This change of paradigm results in a simulation procedure effectively embedding a spectrum-based iterative amplitude-adjusted Fourier transform method devised for continuous processes. The proposed algorithm is fully general, requires minimal assumptions, and can easily simulate binary signals with power-law and exponentially decaying autocorrelation functions corresponding, for instance, to Hurst-Kolmogorov and Markov processes. An application to rainfall intermittency shows that the proposed algorithm can also simulate surrogate data preserving the empirical autocorrelation.
DDC Class
600: Technology