The power of surrogate data testing with respect to non-stationarity

Preprint

29 July 1998

preprint
Published by arXiv in arXiv

https://doi.org/10.48550/arXiv.chao-dyn/9807039

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

SURROGATE DATA TESTING
STATIONARITY SURROGATE
TIME SERIES ANALYSIS
STOCHASTIC PROCESS
CHAOTIC SYSTEM
NONLINEAR

All Related Versions

Version 1, 1998-07-29, ArXiv
Published version: Physical Review E, 58 (4), 5153.

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