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Regresi Kuasa Dua Terkecil Biasa (OLS)×Model Autoregresif Peralihan Licin (STAR)×
BidangEkonometrikEkonometrik
KeluargaRegression modelRegression model
Tahun asal20191994
PengasasWooldridge (textbook treatment); classical least squaresTeräsvirta (1994); van Dijk, Teräsvirta & Franses (2002)
JenisLinear regressionNonlinear time-series regime-switching model
Sumber perintisWooldridge, 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 ↗
Aliasordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonusmooth transition autoregressive model, LSTAR, ESTAR, logistic STAR
Berkaitan54
RingkasanOrdinary 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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ScholarGateBandingkan kaedah: OLS Regression · STAR Model. Dicapai 2026-06-18 daripada https://scholargate.app/ms/compare