Improved Surrogate Data for Nonlinearity Tests.

  title={Improved Surrogate Data for Nonlinearity Tests.},
  author={Schreiber and Schmitz},
  journal={Physical review letters},
  volume={77 4},
  • Schreiber, Schmitz
  • Published 22 July 1996
  • Physics, Mathematics, Medicine
  • Physical review letters
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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