Comparer des méthodes

	Moindres Carrés Pondérés Bayésiens (Bayesian WLS)	Régression bayésienne des moindres carrés ordinaires (Bayesian OLS)
Domaine	Économétrie	Économétrie
Famille	Regression model	Regression model
Année d'origine	1971	1971
Auteur d'origine	Arnold Zellner (Bayesian econometrics framework)	Arnold Zellner
Type	Bayesian weighted regression	Bayesian linear regression
Source fondatrice	Zellner, A. (1971). An Introduction to Bayesian Inference in Econometrics. Wiley, New York. ISBN: 978-0471169376	Zellner, A. (1971). An Introduction to Bayesian Inference in Econometrics. Wiley. ISBN: 978-0471169376
Alias	Bayesian weighted regression, BWLS, Bayesian heteroscedastic regression, weighted Bayesian linear regression	Bayesian linear regression, Bayesian normal regression, BLR, Bayesian least squares
Apparentées	4	5
Résumé	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.	Bayesian OLS combines the classical linear regression likelihood with prior distributions over the coefficients and error variance. Rather than reporting point estimates, it produces full posterior distributions that quantify both estimated effects and their uncertainty. The approach is especially valuable when prior knowledge is available or when samples are small.