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Surrogate testing of linear feedback processes with non-Gaussian innovations

Author

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  • Nagarajan, Radhakrishnan

Abstract

Surrogate testing is used widely to determine the nature of the process generating the given empirical sample. In the present study, the usefulness of phase-randomized surrogates, amplitude adjusted Fourier transform and iterated amplitude adjusted Fourier transform surrogates on statistical inference of linearly correlated noise with non-Gaussian innovations and their static, invertible nonlinear transforms from their empirical samples are discussed. Existing surrogate testing procedures, which retain the auto-correlation function in the surrogates, may not be appropriate in the presence of non-Gaussian innovations.

Suggested Citation

  • Nagarajan, Radhakrishnan, 2006. "Surrogate testing of linear feedback processes with non-Gaussian innovations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 366(C), pages 530-538.
    • Handle: RePEc:eee:phsmap:v:366:y:2006:i:c:p:530-538
    DOI: 10.1016/j.physa.2005.10.041
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    Cited by:

    1. Govindan, R.B. & Wilson, J.D. & Eswaran, H. & Lowery, C.L. & Preißl, H., 2007. "Revisiting sample entropy analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 376(C), pages 158-164.

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