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Bayesian Robust Regression×Quantile Regression×
FachgebietStatistikÖkonometrie
FamilieRegression modelRegression model
Entstehungsjahr19931978
UrheberGeweke (1993); Gelman et al. (2013)Koenker & Bassett
TypBayesian regression with heavy-tailed errorsConditional quantile regression
Wegweisende QuelleGeweke, J. (1993). Bayesian treatment of the independent Student-t linear model. Journal of Applied Econometrics, 8(S1), S19–S40. DOI ↗Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50. DOI ↗
AliasnamenBayesian heavy-tailed regression, Bayesian Student-t regression, robust Bayesian linear model, BRRconditional quantile regression, regression quantiles, Kantil Regresyon
Verwandt65
ZusammenfassungBayesian 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.
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ScholarGateMethoden vergleichen: Bayesian Robust Regression · Quantile Regression. Abgerufen am 2026-06-15 von https://scholargate.app/de/compare