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TAR / SETAR: Autoregresja progowa dla szeregów czasowych ze zmianą reżimu×Regresja progowa×
DziedzinaEkonometriaEkonometria
RodzinaRegression modelRegression model
Rok powstania19902000
TwórcaHowell TongBruce E. Hansen
TypNonlinear time-series model with regime switchingNonlinear regime-switching regression
Źródło pierwotneTong, H. (1990). Non-linear Time Series: A Dynamical System Approach. Oxford University Press. ISBN: 978-0-19-852300-6Hansen, B. E. (2000). Sample Splitting and Threshold Estimation. Econometrica, 68(3), 575-603. DOI ↗
Inne nazwyThreshold Autoregression, Self-Exciting Threshold Autoregression, SETAR Model, Eşik Otoregresyonthreshold model, regime-switching regression, sample splitting model, Eşik Değer Regresyonu (Threshold Regression)
Pokrewne25
PodsumowanieTAR and SETAR are nonlinear autoregressive models introduced by Howell Tong (1990) that allow a time series to follow different linear dynamics in distinct regimes, separated by one or more threshold values. SETAR is the self-exciting variant, in which the threshold variable is a lagged value of the series itself, making it particularly suited to cycles, asymmetric adjustment, and limit-cycle behavior observed in economic and financial data.Threshold regression is a nonlinear, regime-switching model in which the regression parameters take different values above and below an estimated threshold value of a threshold variable. The sample-splitting and threshold-estimation framework was developed by Bruce E. Hansen (2000) and is widely used for time-series and panel data with structural breaks and regime-dependent relationships.
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ScholarGatePorównaj metody: TAR / SETAR · Threshold Regression. Pobrano 2026-06-15 z https://scholargate.app/pl/compare