# Improved Surrogate Data for Nonlinearity Tests.

@article{Schreiber1996ImprovedSD, title={Improved Surrogate Data for Nonlinearity Tests.}, author={Schreiber and Schmitz}, journal={Physical review letters}, year={1996}, volume={77 4}, pages={ 635-638 } }

Current tests for nonlinearity compare a time series to the null hypothesis of a Gaussian linear stochastic process. For this restricted null assumption, random surrogates can be constructed which are constrained by the linear properties of the data. We propose a more general null hypothesis allowing for nonlinear rescalings of a Gaussian linear process. We show that such rescalings cannot be accounted for by a simple amplitude adjustment of the surrogates which leads to spurious detection of…

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