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.Comment: 4 pages, 4 figures, to appear in PR
