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| Квантилна регресия× | Модел на авторегресия с плавен преход (STAR)× | |
|---|---|---|
| Област | Иконометрия | Иконометрия |
| Семейство | Regression model | Regression model |
| Година на възникване≠ | 1978 | 1994 |
| Създател≠ | Koenker & Bassett | Teräsvirta (1994); van Dijk, Teräsvirta & Franses (2002) |
| Тип≠ | Conditional quantile regression | Nonlinear time-series regime-switching model |
| Основополагащ източник≠ | Koenker, 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 ↗ |
| Други названия≠ | conditional quantile regression, regression quantiles, Kantil Regresyon | smooth transition autoregressive model, LSTAR, ESTAR, logistic STAR |
| Свързани≠ | 5 | 4 |
| Резюме≠ | 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. |
| ScholarGateНабор от данни ↗ |
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