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Model Autoregresif Peralihan Licin (STAR)×Regresi Kuantil×
BidangEkonometrikEkonometrik
KeluargaRegression modelRegression model
Tahun asal19941978
PengasasTeräsvirta (1994); van Dijk, Teräsvirta & Franses (2002)Koenker & Bassett
JenisNonlinear time-series regime-switching modelConditional quantile regression
Sumber perintisTeräsvirta, T. (1994). Specification, Estimation, and Evaluation of Smooth Transition Autoregressive Models. Journal of the American Statistical Association, 89(425), 208–218. DOI ↗Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50. DOI ↗
Aliassmooth transition autoregressive model, LSTAR, ESTAR, logistic STARconditional quantile regression, regression quantiles, Kantil Regresyon
Berkaitan45
RingkasanThe 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.
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ScholarGateBandingkan kaedah: STAR Model · Quantile Regression. Dicapai 2026-06-15 daripada https://scholargate.app/ms/compare