Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Квантильная регрессия× | Модель гладкого переходного авторегрессионного процесса (STAR)× | |
|---|---|---|
| Область | Эконометрика | Эконометрика |
| Семейство | Regression model | Regression model |
| Год появления≠ | 1978 | 1994 |
| Автор метода≠ | Koenker & Bassett | Teräsvirta (1994); van Dijk, Teräsvirta & Franses (2002) |
| Тип≠ | Conditional quantile regression | Nonlinear time-series regime-switching model |
| Основополагающий источник≠ | 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 ↗ |
| Другие названия≠ | conditional quantile regression, regression quantiles, Kantil Regresyon | smooth transition autoregressive model, LSTAR, ESTAR, logistic STAR |
| Связанные≠ | 5 | 4 |
| Сводка≠ | 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 данных ↗ |
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