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General simulation algorithm for autocorrelated binary processes

Lookup NU author(s): Dr Francesco Serinaldi

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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0).


Abstract

The apparent ubiquity of binary random processes in physics and many other elds 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 e ectively 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 e ectively embedding 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.


Publication metadata

Author(s): Serinaldi F, Lombardo F

Publication type: Article

Publication status: Published

Journal: Physical Review E

Year: 2017

Volume: 95

Issue: 2

Online publication date: 23/02/2017

Acceptance date: 24/01/2017

Date deposited: 24/01/2017

ISSN (print): 2470-0045

ISSN (electronic): 2470-0053

Publisher: American Physical Society

URL: https://doi.org/10.1103/PhysRevE.95.023312

DOI: 10.1103/PhysRevE.95.023312


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