Work

Revisiting Algorithms for Generating Surrogate Time Series

Year: 2012

Type: article

Abstract: The method of surrogates is one of the key concepts of nonlinear data analysis. Here, we demonstrate that commonly used algorithms for generating surrogates often fail to generate truly linear time series. Rather, they create surrogate realizations with Fourier phase correlations leading to nondetections of nonlinearities. We argue that reliable surrogates can only be generated, if one tests separately for static and dynamic nonlinearities.

Source: Physical Review Letters

DOI: 10.1103/physrevlett.109.144101

Authors: C. Räth, M. Gliozzi, I. E. Papadakis, W. Brinkmann

Institutions: Max Planck Institute for Extraterrestrial Physics, George Mason University, University of Crete, Foundation for Research and Technology Hellas, Max Planck Society

Language: English

Topic: Complex Systems and Time Series Analysis

Subfield: Economics and Econometrics

Field: Economics, Econometrics and Finance

Domain: Social Sciences

Open Access status: green

Funder: National Aeronautics and Space Administration

OpenAlex ID: W1980521058

FWCI: 4.524

Cites: 18

Cited by: 30

Related to: 10