Toggle Main Menu Toggle Search

Open Access padlockePrints

General simulation algorithm for autocorrelated binary processes

Lookup NU author(s): Dr Francesco Serinaldi



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


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


DOI: 10.1103/PhysRevE.95.023312


Altmetrics provided by Altmetric