Test your surrogate data before you test for nonlinearity.

  title={Test your surrogate data before you test for nonlinearity.},
  author={Dimitris Kugiumtzis},
  journal={Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics},
  volume={60 3},
  • D. Kugiumtzis
  • Published 7 May 1999
  • Computer Science
  • Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics
The schemes for the generation of surrogate data in order to test the null hypothesis of linear stochastic process undergoing nonlinear static transform are investigated as to their consistency in representing the null hypothesis. In particular, we pinpoint some important caveats of the prominent algorithm of amplitude adjusted Fourier transform surrogates (AAFT) and compare it to the iterated AAFT, which is more consistent in representing the null hypothesis. It turns out that in many… 

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