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Solidny Model Autoregresyjny Rozłożony na Długach (Robust NARDL)×Regresja kwantylowa×
DziedzinaEkonometriaEkonometria
RodzinaRegression modelRegression model
Rok powstania2014–2020s1978
TwórcaExtension of Shin, Yu & Greenwood-Nimmo (2014) NARDL framework with robust (outlier-resistant) estimationKoenker & Bassett
TypNonlinear time-series regression with robust estimationConditional quantile regression
Źródło pierwotneShin, Y., Yu, B., & Greenwood-Nimmo, M. (2014). Modelling asymmetric cointegration and dynamic multipliers in a nonlinear ARDL framework. In W. C. Horrace & R. C. Sickles (Eds.), Festschrift in Honor of Peter Schmidt (pp. 281–314). Springer. DOI ↗Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50. DOI ↗
Inne nazwyRobust Nonlinear ARDL, Outlier-Robust NARDL, Robust Asymmetric ARDL, R-NARDLconditional quantile regression, regression quantiles, Kantil Regresyon
Pokrewne35
PodsumowanieRobust NARDL marries the asymmetric cointegration framework of Shin, Yu, and Greenwood-Nimmo (2014) with outlier-resistant estimation. It decomposes a regressor into positive and negative partial sums, tests for asymmetric long-run relationships via a bounds test, and replaces the OLS criterion with an M- or MM-estimator to guard against leverage points and additive outliers common in macroeconomic and financial time series.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.
ScholarGateZbiór danych
  1. v1
  2. 2 Źródła
  3. PUBLISHED
  1. v1
  2. 2 Źródła
  3. PUBLISHED

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ScholarGatePorównaj metody: Robust NARDL · Quantile Regression. Pobrano 2026-06-15 z https://scholargate.app/pl/compare