Сравнение на методи

	Квантилна регресия	Robust OLS (OLS с робастни стандартни грешки)
Област	Иконометрия	Иконометрия
Семейство	Regression model	Regression model
Година на възникване	1978	1980
Създател	Koenker & Bassett	Halbert White
Тип	Conditional quantile regression	Linear regression with robust inference
Основополагащ източник	Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50.	White, H. (1980). A heteroskedasticity-consistent covariance matrix estimator and a direct test for heteroskedasticity. Econometrica, 48(4), 817–838.
Други названия	conditional quantile regression, regression quantiles, Kantil Regresyon	HC robust regression, White robust OLS, sandwich estimator OLS, OLS with robust standard errors
Свързани	5	6
Резюме	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.	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.