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Kvantilregression×Robust OLS (OLS med robusta standardfel)×
ÄmnesområdeEkonometriEkonometri
FamiljRegression modelRegression model
Ursprungsår19781980
UpphovspersonKoenker & BassettHalbert White
TypConditional quantile regressionLinear regression with robust inference
UrsprungskällaKoenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50. DOI ↗White, H. (1980). A heteroskedasticity-consistent covariance matrix estimator and a direct test for heteroskedasticity. Econometrica, 48(4), 817–838. DOI ↗
Aliasconditional quantile regression, regression quantiles, Kantil RegresyonHC robust regression, White robust OLS, sandwich estimator OLS, OLS with robust standard errors
Närliggande56
SammanfattningQuantile 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 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.
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  1. v1
  2. 2 Källor
  3. PUBLISHED

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ScholarGateJämför metoder: Quantile Regression · Robust OLS. Hämtad 2026-06-18 från https://scholargate.app/sv/compare