Bivariate bilinear models and their specification

Research output: Chapter in Book/Report/Conference proceedingChapterResearchpeer-review

Abstract

It should be noted that for linear bivariate models, the third order cross moments γ
xy (k, 1)= 0 for all k and 1. Hence looking at a table of the third order cross moments one can
easily distinguish bivariate bilinear models from linear bivariate models (assuming the
distribution of noise is Gaussian and series xt had been prewhitened). Again, one can also
distinguish between Tables 2, 3, and 4, ie, between diagonal, subdiagonal, and
superdiagonal bivariate bilinear models by looking at these tables. It may also be possible to
distinguish the lags of the particular model by carefully looking at the table. It may be more
interesting to look at the third order cross moment table for a few more general bivariate
bilinear models.
Original languageEnglish
Title of host publicationNonlinear Time Series and Signal Processing
EditorsR R Mohler
Place of PublicationBerlin
PublisherSpringer
Pages59-74
Number of pages15
ISBN (Electronic)978-3-540-38837-1
ISBN (Print)978-3-540-18861-2
DOIs
Publication statusPublished - 1988
Externally publishedYes

Publication series

NameLecture Notes in Control and Information Sciences
Volume106
ISSN (Print)0170-8643

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Cite this

Kumar, K. (1988). Bivariate bilinear models and their specification. In R. R. Mohler (Ed.), Nonlinear Time Series and Signal Processing (pp. 59-74). (Lecture Notes in Control and Information Sciences; Vol. 106). Berlin: Springer. https://doi.org/10.1007/BFb0044275
Kumar, Kuldeep. / Bivariate bilinear models and their specification. Nonlinear Time Series and Signal Processing. editor / R R Mohler. Berlin : Springer, 1988. pp. 59-74 (Lecture Notes in Control and Information Sciences).
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abstract = "It should be noted that for linear bivariate models, the third order cross moments γ xy (k, 1)= 0 for all k and 1. Hence looking at a table of the third order cross moments one can easily distinguish bivariate bilinear models from linear bivariate models (assuming the distribution of noise is Gaussian and series xt had been prewhitened). Again, one can also distinguish between Tables 2, 3, and 4, ie, between diagonal, subdiagonal, and superdiagonal bivariate bilinear models by looking at these tables. It may also be possible to distinguish the lags of the particular model by carefully looking at the table. It may be more interesting to look at the third order cross moment table for a few more general bivariate bilinear models.",
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Kumar, K 1988, Bivariate bilinear models and their specification. in RR Mohler (ed.), Nonlinear Time Series and Signal Processing. Lecture Notes in Control and Information Sciences, vol. 106, Springer, Berlin, pp. 59-74. https://doi.org/10.1007/BFb0044275

Bivariate bilinear models and their specification. / Kumar, Kuldeep.

Nonlinear Time Series and Signal Processing. ed. / R R Mohler. Berlin : Springer, 1988. p. 59-74 (Lecture Notes in Control and Information Sciences; Vol. 106).

Research output: Chapter in Book/Report/Conference proceedingChapterResearchpeer-review

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Kumar K. Bivariate bilinear models and their specification. In Mohler RR, editor, Nonlinear Time Series and Signal Processing. Berlin: Springer. 1988. p. 59-74. (Lecture Notes in Control and Information Sciences). https://doi.org/10.1007/BFb0044275