Comparer des méthodes

	Régression Robuste Bayésienne	Régression quantile
Domaine	Statistique	Économétrie
Famille	Regression model	Regression model
Année d'origine	1993	1978
Auteur d'origine	Geweke (1993); Gelman et al. (2013)	Koenker & Bassett
Type	Bayesian regression with heavy-tailed errors	Conditional quantile regression
Source fondatrice	Geweke, J. (1993). Bayesian treatment of the independent Student-t linear model. Journal of Applied Econometrics, 8(S1), S19–S40.	Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50.
Alias	Bayesian heavy-tailed regression, Bayesian Student-t regression, robust Bayesian linear model, BRR	conditional quantile regression, regression quantiles, Kantil Regresyon
Apparentées	6	5
Résumé	Bayesian Robust Regression replaces the Gaussian error assumption of ordinary linear regression with a heavy-tailed distribution — most commonly the Student-t — and estimates all parameters in a Bayesian framework. The heavier tails give outliers less influence on the fitted line, yielding stable coefficient estimates and honest uncertainty intervals even when the data contain unusual 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.