HOS or SOS for parametric modeling?

G. B. Giannakis, M. K. Tsatsanis

Research output: Chapter in Book/Report/Conference proceedingConference contribution

13 Scopus citations

Abstract

Parametric models obtained via second-order statistics (SOS) are appropriate when the available stationary data are linear, Gaussian, and time-reversible. On the other hand, evidence of nonlinearity, non-Gaussianity, or time-irreversibility favors the use of higher-order statistics (HOS). To quantify normality and time-reversibility, and thus resolve the title question, consistent, time-domain statistical tests are developed and analyzed in a Neyman-Pearson framework. The novel test statistics are computationally attractive and streamlined towards parametric modeling because they employ the minimal HOS lags which uniquely characterize autoregressive moving-average processes. Simulations illustrate the performance of the proposed tests.

Original languageEnglish (US)
Title of host publicationProceedings - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing
PublisherPubl by IEEE
Pages3097-3100
Number of pages4
ISBN (Print)0780300033
DOIs
StatePublished - 1991
EventProceedings of the 1991 International Conference on Acoustics, Speech, and Signal Processing - ICASSP 91 - Toronto, Ont, Can
Duration: May 14 1991May 17 1991

Publication series

NameProceedings - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing
Volume5
ISSN (Print)0736-7791

Other

OtherProceedings of the 1991 International Conference on Acoustics, Speech, and Signal Processing - ICASSP 91
CityToronto, Ont, Can
Period5/14/915/17/91

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  • Cite this

    Giannakis, G. B., & Tsatsanis, M. K. (1991). HOS or SOS for parametric modeling? In Proceedings - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing (pp. 3097-3100). (Proceedings - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing; Vol. 5). Publ by IEEE. https://doi.org/10.1109/icassp.1991.150110