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Regresija običnih najmanjih kvadrata (OLS)×Model glatke prijelazne autoregresije (STAR)×
PodručjeEkonometrijaEkonometrija
ObiteljRegression modelRegression model
Godina nastanka20191994
TvoracWooldridge (textbook treatment); classical least squaresTeräsvirta (1994); van Dijk, Teräsvirta & Franses (2002)
VrstaLinear regressionNonlinear time-series regime-switching model
Temeljni izvorWooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860Teräsvirta, T. (1994). Specification, Estimation, and Evaluation of Smooth Transition Autoregressive Models. Journal of the American Statistical Association, 89(425), 208–218. DOI ↗
Drugi naziviordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonusmooth transition autoregressive model, LSTAR, ESTAR, logistic STAR
Srodne54
SažetakOrdinary 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).The 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.
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ScholarGateUsporedite metode: OLS Regression · STAR Model. Preuzeto 2026-06-18 s https://scholargate.app/hr/compare