Copula-based algorithm for generating bursty time series
Loading...
Access rights
openAccess
Journal Title
Journal ISSN
Volume Title
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
This publication is imported from Aalto University research portal.
View publication in the Research portal
View/Open full text file from the Research portal
Other link related to publication
View publication in the Research portal
View/Open full text file from the Research portal
Other link related to publication
Date
2019-08-14
Department
Major/Subject
Mcode
Degree programme
Language
en
Pages
1-6
Series
Physical Review E, Volume 100, issue 2
Abstract
Dynamical processes in various natural and social phenomena have been described by a series of events or event sequences showing non-Poissonian, bursty temporal patterns. Temporal correlations in such bursty time series can be understood not only by heterogeneous interevent times (IETs) but also by correlations between IETs. Modeling and simulating various dynamical processes requires us to generate event sequences with a heavy-tailed IET distribution and memory effects between IETs. For this, we propose a Farlie-Gumbel-Morgenstern copula-based algorithm for generating event sequences with correlated IETs when the IET distribution and the memory coefficient between two consecutive IETs are given. We successfully apply our algorithm to the cases with heavy-tailed IET distributions. We also compare our algorithm to the existing shuffling method to find that our algorithm outperforms the shuffling method for some cases. Our copula-based algorithm is expected to be used for more realistic modeling of various dynamical processes.Description
Keywords
Other note
Citation
Jo, H H, Lee, B H, Hiraoka, T & Jung, W S 2019, ' Copula-based algorithm for generating bursty time series ', Physical Review E, vol. 100, no. 2, 022307, pp. 1-6 . https://doi.org/10.1103/PhysRevE.100.022307
