Vertaile menetelmiä

	OLS-regressio (Ordinary Least Squares)	Sileän siirtymän autoregressiivinen (STAR) malli
Tieteenala	Ekonometria	Ekonometria
Menetelmäperhe	Regression model	Regression model
Syntyvuosi	2019	1994
Kehittäjä	Wooldridge (textbook treatment); classical least squares	Teräsvirta (1994); van Dijk, Teräsvirta & Franses (2002)
Tyyppi	Linear regression	Nonlinear time-series regime-switching model
Alkuperäislähde	Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860	Teräsvirta, T. (1994). Specification, Estimation, and Evaluation of Smooth Transition Autoregressive Models. Journal of the American Statistical Association, 89(425), 208–218.
Rinnakkaisnimet	ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu	smooth transition autoregressive model, LSTAR, ESTAR, logistic STAR
Liittyvät	5	4
Tiivistelmä	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).	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.