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Model glatke tranzicije (STAR)×Regresija običnih najmanjih kvadrata (OLS)×
OblastEkonometrijaEkonometrija
PorodicaRegression modelRegression model
Godina nastanka19942019
TvoracTeräsvirta (1994); van Dijk, Teräsvirta & Franses (2002)Wooldridge (textbook treatment); classical least squares
TipNonlinear time-series regime-switching modelLinear 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 ↗Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860
Drugi nazivismooth transition autoregressive model, LSTAR, ESTAR, logistic STARordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu
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.Ordinary Least Squares is the classical linear regression method that explains a continuous outcome as a linear combination of predictors. It estimates the coefficients by minimising the sum of squared residuals, and under the Gauss-Markov assumptions these estimates are the best linear unbiased estimator (BLUE).
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ScholarGateUporedite metode: STAR Model · OLS Regression. Preuzeto 2026-06-15 sa https://scholargate.app/sr/compare