قارن الطرق

	نموذج الانحدار الذاتي الانتقالي السلس (STAR)	انحدار المربعات الصغرى العادية (OLS)
المجال	الاقتصاد القياسي	الاقتصاد القياسي
العائلة	Regression model	Regression model
سنة النشأة	1994	2019
صاحب الطريقة	Teräsvirta (1994); van Dijk, Teräsvirta & Franses (2002)	Wooldridge (textbook treatment); classical least squares
النوع	Nonlinear time-series regime-switching model	Linear regression
المصدر التأسيسي	Teräsvirta, T. (1994). Specification, Estimation, and Evaluation of Smooth Transition Autoregressive Models. Journal of the American Statistical Association, 89(425), 208–218.	Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860
الأسماء البديلة	smooth transition autoregressive model, LSTAR, ESTAR, logistic STAR	ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu
ذات صلة	4	5
الملخص	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.	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).