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Robust OLS (OLS, jossa robustit keskivirheet)×Kvanttiiliregressio×
TieteenalaEkonometriaEkonometria
MenetelmäperheRegression modelRegression model
Syntyvuosi19801978
KehittäjäHalbert WhiteKoenker & Bassett
TyyppiLinear regression with robust inferenceConditional quantile regression
AlkuperäislähdeWhite, H. (1980). A heteroskedasticity-consistent covariance matrix estimator and a direct test for heteroskedasticity. Econometrica, 48(4), 817–838. DOI ↗Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50. DOI ↗
RinnakkaisnimetHC robust regression, White robust OLS, sandwich estimator OLS, OLS with robust standard errorsconditional quantile regression, regression quantiles, Kantil Regresyon
Liittyvät65
TiivistelmäRobust OLS applies ordinary least squares to estimate coefficients and then replaces the classical standard errors with heteroscedasticity-consistent (HC) standard errors — commonly called White standard errors. This leaves the point estimates unchanged while yielding valid t-statistics and confidence intervals even when the error variance is not constant across observations.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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ScholarGateVertaile menetelmiä: Robust OLS · Quantile Regression. Haettu 2026-06-17 osoitteesta https://scholargate.app/fi/compare