2005
DOI: 10.1109/tsp.2004.838942
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A time-domain test for some types of nonlinearity

Abstract: Abstract-The bispectrum and third-order moment can be viewed as equivalent tools for testing for the presence of nonlinearity in stationary time series. This is because the bispectrum is the Fourier transform of the third-order moment. An advantage of the bispectrum is that its estimator comprises terms that are asymptotically independent at distinct bifrequencies under the null hypothesis of linearity. An advantage of the third-order moment is that its values in any subset of joint lags can be used in the tes… Show more

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Cited by 63 publications
(52 citation statements)
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“…measure of symmetry around the mean of the time series, of the original with the surrogate time series based on test statistics, see [31,34,35].…”
Section: Aaft Methodsmentioning
confidence: 99%
See 1 more Smart Citation
“…measure of symmetry around the mean of the time series, of the original with the surrogate time series based on test statistics, see [31,34,35].…”
Section: Aaft Methodsmentioning
confidence: 99%
“…The bootstrapping method from [34], aims to find a third-order estimate in the region 0 ≤ ξ 1 ≤ ξ 2 ≤ M , with M as a truncation value (1 ≤ M ≤ N ). The integers ξ 1 and ξ 2 define the serial indicates for the calculation of the third-order moments, i.e.…”
Section: Aaft Methodsmentioning
confidence: 99%
“…There are many published reports, especially in recent years, that utilize the bootstrap in linearity testing, e.g., Barnett and Wolff (2005), Birkelund and Hanssen (2009), Hinich et al (2005), Hjellvik and Tjostheim (1995), Kugiumtzis (2008). Our approach is fundamentally different from these previous works although some similarities are present.…”
Section: Introductionmentioning
confidence: 92%
“…The typical null being that the series under consideration is both linear and stationary, a rejection could be either in the direction of nonlinearity, nonstationarity or both. Recent attempts to separate nonlinearity and nonstationarity via so-called phase scrambled bootstrap methods (Aparicio (1998), Kugimutzis (2001) and Barnett and Wolff (2005)) have not been very successful. Method V attempts to meet this challenging task by attempting to model both the nonlinear and possibly nonstationary features of the data simultaneously, by making the coefficients time varying in a deterministic fashion.…”
Section: Sunspot Datamentioning
confidence: 99%