Issue |
EPL
Volume 91, Number 3, August 2010
|
|
---|---|---|
Article Number | 30005 | |
Number of page(s) | 5 | |
Section | General | |
DOI | https://doi.org/10.1209/0295-5075/91/30005 | |
Published online | 27 August 2010 |
Fast detection of nonlinearity and nonstationarity in short and noisy time series
Laboratorio sui Sistemi Complessi, Scuola Superiore di Catania - Via San Nullo 5/i, 95123 Catania, Italy, EU and Dipartimento di Fisica e Astronomia, Università di Catania, and INFN - Via S. Sofia 64, 95123 Catania, Italy, EU
a
manlio.dedomenico@ct.infn.it
Received:
9
June
2010
Accepted:
31
July
2010
We introduce a statistical method to detect nonlinearity and nonstationarity in time series, that works even for short sequences and in the presence of noise. The method has a discrimination power similar to that of the most advanced estimators on the market, yet it depends only on one parameter, is easier to implement and faster. Applications to real data sets reject the null hypothesis of an underlying stationary linear stochastic process with a higher confidence interval than the best known nonlinear discriminators up to date.
PACS: 05.45.Tp – Time series analysis / 05.10.-a – Computational methods in statistical physics and nonlinear dynamics
© EPLA, 2010
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.