Methoden vergleichen

	Bayesian Weighted Least Squares (Bayesian WLS)	Robust Weighted Least Squares (Robust WLS)
Fachgebiet	Ökonometrie	Ökonometrie
Familie	Regression model	Regression model
Entstehungsjahr	1971	1964/1981
Urheber	Arnold Zellner (Bayesian econometrics framework)	Huber, P. J.
Typ	Bayesian weighted regression	Robust weighted regression
Wegweisende Quelle	Zellner, A. (1971). An Introduction to Bayesian Inference in Econometrics. Wiley, New York. ISBN: 978-0471169376	Huber, P. J. (1981). Robust Statistics. Wiley. ISBN: 978-0471418054
Aliasnamen	Bayesian weighted regression, BWLS, Bayesian heteroscedastic regression, weighted Bayesian linear regression	robust weighted least squares, RWLS, heteroscedasticity-robust WLS, outlier-robust weighted regression
Verwandt	4	5
Zusammenfassung	Bayesian Weighted Least Squares combines the classical WLS weighting scheme — which downweights observations with high error variance — with Bayesian prior distributions over the regression coefficients and error variance. The result is a posterior distribution that reflects both the data likelihood and prior beliefs, providing full uncertainty quantification in heteroscedastic settings.	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.