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Nelinearni autoregresijski (NAR) model×Nelinearni vektorski model korekcije pogreške (Nonlinear VECM)×
PodručjeEkonometrijaEkonometrija
ObiteljRegression modelRegression model
Godina nastanka1978-19901989–1998
TvoracTong, H. (threshold AR); Terasvirta, T. (STAR variant)Granger & Lee (1989); Enders & Granger (1998)
VrstaNonlinear time series modelNonlinear time-series model
Temeljni izvorTong, H. (1990). Non-Linear Time Series: A Dynamical System Approach. Oxford University Press. ISBN: 9780198522201Enders, W., & Granger, C. W. J. (1998). Unit-root tests and asymmetric adjustment with an example using the term structure of interest rates. Journal of Business & Economic Statistics, 16(3), 304–311. DOI ↗
Drugi naziviNAR model, nonlinear autoregression, NLAR, threshold autoregressive modelnonlinear VECM, NVECM, threshold VECM, asymmetric VECM
Srodne62
SažetakThe Nonlinear AR model extends the classical autoregressive framework by allowing the mapping from past values to the current value to follow an arbitrary or regime-switching nonlinear function. Major families include the Self-Exciting Threshold AR (SETAR), Smooth Transition AR (STAR), and neural network AR, each capturing different forms of asymmetry, regime shifts, or smooth nonlinear dynamics in univariate time series.The Nonlinear VECM extends the standard linear VECM by allowing the speed of adjustment toward long-run equilibrium to differ depending on the sign, magnitude, or regime of deviations from that equilibrium. It captures asymmetric or threshold-driven dynamics in cointegrated time-series systems that a standard VECM would miss.
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ScholarGateUsporedite metode: Nonlinear AR Model · Nonlinear VECM. Preuzeto 2026-06-17 s https://scholargate.app/hr/compare