Surrogate testing of linear feedback processes with non-Gaussian innovations

Radhakrishnan Nagarajan

Physica A: Statistical Mechanics and its Applications, 2006, vol. 366, issue C, 530-538

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.

Keywords: Linear feedback process; Surrogate testing; Approximate entropy (search for similar items in EconPapers)
Date: 2006
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378437105011295
Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:366:y:2006:i:c:p:530-538

DOI: 10.1016/j.physa.2005.10.041

Access Statistics for this article

Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis

More articles in Physica A: Statistical Mechanics and its Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().