The power of surrogate data testing with respect to non-stationarity
chao-dyn
2009-10-31 v1 Chaotic Dynamics
Abstract
Surrogate data testing is a method frequently applied to evaluate the results of nonlinear time series analysis. Since the null hypothesis tested against is a linear, gaussian, stationary stochastic process a positive outcome may not only result from an underlying nonlinear or even chaotic system, but also from e.g. a non-stationary linear one. We investigate the power of the test against non-stationarity.
Keywords
Cite
@article{arxiv.chao-dyn/9807039,
title = {The power of surrogate data testing with respect to non-stationarity},
author = {J. Timmer},
journal= {arXiv preprint arXiv:chao-dyn/9807039},
year = {2009}
}
Comments
4 pages, 4 figures, to appear in PRE