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Regressão Quantílica×Modelo Autorregressivo de Transição Suave (STAR)×
ÁreaEconometriaEconometria
FamíliaRegression modelRegression model
Ano de origem19781994
Autor originalKoenker & BassettTeräsvirta (1994); van Dijk, Teräsvirta & Franses (2002)
TipoConditional quantile regressionNonlinear time-series regime-switching model
Fonte seminalKoenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50. DOI ↗Teräsvirta, T. (1994). Specification, Estimation, and Evaluation of Smooth Transition Autoregressive Models. Journal of the American Statistical Association, 89(425), 208–218. DOI ↗
Outros nomesconditional quantile regression, regression quantiles, Kantil Regresyonsmooth transition autoregressive model, LSTAR, ESTAR, logistic STAR
Relacionados54
ResumoQuantile 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.
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ScholarGateComparar métodos: Quantile Regression · STAR Model. Recuperado em 2026-06-18 de https://scholargate.app/pt/compare