เปรียบเทียบวิธี

	แบบจำลอง STAR (Smooth Transition Autoregressive Model)	การถดถอยควอนไทล์
สาขาวิชา	เศรษฐมิติ	เศรษฐมิติ
ตระกูล	Regression model	Regression model
ปีกำเนิด	1994	1978
ผู้ริเริ่ม	Teräsvirta (1994); van Dijk, Teräsvirta & Franses (2002)	Koenker & Bassett
ประเภท	Nonlinear time-series regime-switching model	Conditional quantile regression
แหล่งต้นตำรับ	Teräsvirta, T. (1994). Specification, Estimation, and Evaluation of Smooth Transition Autoregressive Models. Journal of the American Statistical Association, 89(425), 208–218.	Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50.
ชื่อเรียกอื่น	smooth transition autoregressive model, LSTAR, ESTAR, logistic STAR	conditional quantile regression, regression quantiles, Kantil Regresyon
ที่เกี่ยวข้อง	4	5
สรุป	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.	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.