Compară metode

	Regresia cuantilică	Modelul Autoregresiv cu Tranziție Lină (STAR)
Domeniu	Econometrie	Econometrie
Familie	Regression model	Regression model
Anul apariției	1978	1994
Autorul original	Koenker & Bassett	Teräsvirta (1994); van Dijk, Teräsvirta & Franses (2002)
Tip	Conditional quantile regression	Nonlinear time-series regime-switching model
Sursa seminală	Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50.	Teräsvirta, T. (1994). Specification, Estimation, and Evaluation of Smooth Transition Autoregressive Models. Journal of the American Statistical Association, 89(425), 208–218.
Denumiri alternative	conditional quantile regression, regression quantiles, Kantil Regresyon	smooth transition autoregressive model, LSTAR, ESTAR, logistic STAR
Înrudite	5	4
Rezumat	Quantile regression models conditional quantiles of an outcome - the median, the 25th or 75th percentile, and so on - rather than the conditional mean that OLS targets. Introduced by Koenker and Bassett in 1978, it reveals how predictors act across the whole distribution, including its tails.	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.