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Regresia cuantilică×Regresie Liniară Generalizată Robustă (Robust GLS)×
DomeniuEconometrieEconometrie
FamilieRegression modelRegression model
Anul apariției19781936 / 1980
Autorul originalKoenker & BassettAitken (GLS theory, 1936); White (robust covariance, 1980)
TipConditional quantile regressionRobust linear regression
Sursa seminalăKoenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50. DOI ↗Greene, W. H. (2012). Econometric Analysis (7th ed.). Pearson. Chapter 9: The Generalized Regression Model and Heteroscedasticity. ISBN: 978-0131395381
Denumiri alternativeconditional quantile regression, regression quantiles, Kantil Regresyonrobust generalized least squares, GLS with robust standard errors, heteroscedasticity-consistent GLS, HC-GLS
Înrudite55
RezumatQuantile 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.Robust GLS extends classical Generalized Least Squares by pairing GLS coefficient estimation with heteroscedasticity- and autocorrelation-consistent (HAC) standard errors, or by using M-estimation within the GLS framework. It corrects for non-spherical errors — heteroscedasticity, autocorrelation, or both — while also guarding inference against misspecification of the error covariance structure.
ScholarGateSet de date
  1. v1
  2. 2 Surse
  3. PUBLISHED
  1. v1
  2. 2 Surse
  3. PUBLISHED

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ScholarGateCompară metode: Quantile Regression · Robust GLS. Preluat la 2026-06-18 de pe https://scholargate.app/ro/compare