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Model glatke prijelazne autoregresije (STAR)×Kvantilna regresija×
PodručjeEkonometrijaEkonometrija
ObiteljRegression modelRegression model
Godina nastanka19941978
TvoracTeräsvirta (1994); van Dijk, Teräsvirta & Franses (2002)Koenker & Bassett
VrstaNonlinear time-series regime-switching modelConditional quantile regression
Temeljni izvorTeräsvirta, T. (1994). Specification, Estimation, and Evaluation of Smooth Transition Autoregressive Models. Journal of the American Statistical Association, 89(425), 208–218. DOI ↗Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50. DOI ↗
Drugi nazivismooth transition autoregressive model, LSTAR, ESTAR, logistic STARconditional quantile regression, regression quantiles, Kantil Regresyon
Srodne45
SažetakThe 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.Quantile regression models conditional quantiles of an outcome - the median, the 25th or 75th percentile, and so on - rather than the conditional mean that OLS targets. Introduced by Koenker and Bassett in 1978, it reveals how predictors act across the whole distribution, including its tails.
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ScholarGateUsporedite metode: STAR Model · Quantile Regression. Preuzeto 2026-06-17 s https://scholargate.app/hr/compare