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Mūsdienu pārejas autoregresijas (STAR) modelis×Regresija ar slieksni×
NozareEkonometrijaEkonometrija
SaimeRegression modelRegression model
Izcelsmes gads19942000
AutorsTeräsvirta (1994); van Dijk, Teräsvirta & Franses (2002)Bruce E. Hansen
TipsNonlinear time-series regime-switching modelNonlinear regime-switching regression
PirmavotsTeräsvirta, T. (1994). Specification, Estimation, and Evaluation of Smooth Transition Autoregressive Models. Journal of the American Statistical Association, 89(425), 208–218. DOI ↗Hansen, B. E. (2000). Sample Splitting and Threshold Estimation. Econometrica, 68(3), 575-603. DOI ↗
Citi nosaukumismooth transition autoregressive model, LSTAR, ESTAR, logistic STARthreshold model, regime-switching regression, sample splitting model, Eşik Değer Regresyonu (Threshold Regression)
Saistītās45
KopsavilkumsThe Smooth Transition Autoregressive (STAR) model is a nonlinear time-series model, developed in Teräsvirta's 1994 framework, that lets the dynamics move smoothly rather than abruptly between two regimes. The logistic variant (LSTAR) captures asymmetric business cycles and the exponential variant (ESTAR) captures purchasing-power-parity deviations.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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ScholarGateSalīdzināt metodes: STAR Model · Threshold Regression. Izgūts 2026-06-17 no https://scholargate.app/lv/compare