SURROGATE DATA FOR NON–STATIONARY SIGNALS

@inproceedings{Schmitz2000SURROGATEDF,
  title={SURROGATE DATA FOR NON–STATIONARY SIGNALS},
  author={A. Schmitz and Thomas Schreiber},
  year={2000}
}
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 non–linearity 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. 

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