Surrogate data for non-stationary signals
chao-dyn
2007-05-23 v1 Chaotic Dynamics
Abstract
Standard tests for nonlinearity reject the null hypothesis of a Gaussian linear process whenever the data is non-stationary. Thus, they are not appropriate to distinguish nonlinearity from non-stationarity. We address the problem of generating proper surrogate data corresponding to the null hypothesis of an ARMA process with slowly varying coefficients.
Cite
@article{arxiv.chao-dyn/9904023,
title = {Surrogate data for non-stationary signals},
author = {Andreas Schmitz and Thomas Schreiber},
journal= {arXiv preprint arXiv:chao-dyn/9904023},
year = {2007}
}
Comments
4 pages, 4 figures. proceeding for a poster