Compara mètodes

	Mínims Quadrats Ponderats Robuts (Robust WLS)	Regressió quantílica
Camp	Econometria	Econometria
Família	Regression model	Regression model
Any d'origen	1964/1981	1978
Autor original	Huber, P. J.	Koenker & Bassett
Tipus	Robust weighted regression	Conditional quantile regression
Font seminal	Huber, P. J. (1981). Robust Statistics. Wiley. ISBN: 978-0471418054	Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50.
Àlies	robust weighted least squares, RWLS, heteroscedasticity-robust WLS, outlier-robust weighted regression	conditional quantile regression, regression quantiles, Kantil Regresyon
Relacionats	5	5
Resum	Robust WLS combines weighted least squares — which corrects for known or estimated heteroscedasticity — with robust M-estimation that down-weights influential outliers. The result is a regression estimator that is simultaneously efficient under non-constant error variance and resistant to observations that would otherwise distort coefficient estimates.	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.