Surrogate testing of linear feedback processes with non-Gaussian innovations
Statistical Mechanics
2007-05-23 v2 Chaotic Dynamics
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 (AAFT) and iterated amplitude adjusted Fourier transform (IAAFT) surrogates on statistical inference of linearly correlated noise with non-Gaussian innovations and their static, invertible nonlinear transforms from their empirical samples is 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.
Keywords
Cite
@article{arxiv.cond-mat/0510517,
title = {Surrogate testing of linear feedback processes with non-Gaussian innovations},
author = {Radhakrishnan Nagarajan},
journal= {arXiv preprint arXiv:cond-mat/0510517},
year = {2007}
}
Comments
18 Pages, 6 Figures, Appendix