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Robustní regresní analýza kvantilů×Kvantilová regrese×
OborStatistikaEkonometrie
RodinaRegression modelRegression model
Rok vzniku1993–19971978
TvůrceKoenker & Bassett (1978); robust extensions by Machado (1993) and He (1997)Koenker & Bassett
TypRobust semiparametric regressionConditional quantile regression
Původní zdrojKoenker, R. (2005). Quantile Regression. Cambridge University Press. ISBN: 978-0521608275Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50. DOI ↗
Další názvyrobust QR, outlier-resistant quantile regression, bounded-influence quantile regression, RQRconditional quantile regression, regression quantiles, Kantil Regresyon
Příbuzné65
ShrnutíRobust Quantile Regression estimates conditional quantiles of a response variable while simultaneously downweighting the influence of outliers. By combining the asymmetric loss function of standard quantile regression with bounded-influence or M-estimation weights, it provides reliable quantile estimates even when data contain extreme observations or heavy-tailed error distributions.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.
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ScholarGatePorovnat metody: Robust Quantile Regression · Quantile Regression. Získáno 2026-06-15 z https://scholargate.app/cs/compare