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Regresija s vremenski promjenjivim parametrima na kvantilima (TVP-QQ)×Kvantilno-na-kvantilna (QQ) regresija×
PodručjeEkonometrijaEkonometrija
ObiteljRegression modelRegression model
Godina nastanka2015–20192015
TvoracExtension of Sim & Zhou (2015) QQ framework; TVP adaptation by subsequent applied econometriciansSim and Zhou
VrstaNonparametric time-varying quantile regressionNonparametric quantile regression
Temeljni izvorSim, N., & Zhou, H. (2015). Oil prices, US stock return, and the dependence between their quantiles. Journal of Banking & Finance, 55, 1–8. DOI ↗Sim, N., & Zhou, H. (2015). Oil prices, US stock return, and the dependence between their quantiles. Journal of Banking and Finance, 55, 1-8. DOI ↗
Drugi naziviTVP-QQ regression, time-varying QQ regression, dynamic quantile-on-quantile regression, TVP quantile-on-quantileQQ regression, QQ approach, quantile-on-quantile approach, nonparametric quantile regression
Srodne26
SažetakTVP-QQ regression extends the quantile-on-quantile (QQ) framework by allowing the slope coefficients to evolve over time. It maps how the quantiles of a predictor variable affect the quantiles of an outcome differently across the joint distribution and across different time periods, uncovering dynamic, heterogeneous dependence structures that standard regression cannot detect.Quantile-on-quantile regression is a nonparametric technique that estimates how the quantiles of one variable depend on the quantiles of another. By combining standard quantile regression with local linear smoothing, it produces a full two-dimensional surface of slope coefficients indexed by both the quantile of the outcome and the quantile of the predictor, revealing heterogeneous and asymmetric dependency structures invisible to standard regression.
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ScholarGateUsporedite metode: Time-varying parameter quantile-on-quantile regression · Quantile-on-Quantile Regression. Preuzeto 2026-06-18 s https://scholargate.app/hr/compare