Сравнение на методи

	Байесов метод на най-малките квадрати с тегла (Bayesian WLS)	Байесова ОЛС (Байесова обикновена най-малка квадратична регресия)
Област	Иконометрия	Иконометрия
Семейство	Regression model	Regression model
Година на възникване	1971	1971
Създател	Arnold Zellner (Bayesian econometrics framework)	Arnold Zellner
Тип	Bayesian weighted regression	Bayesian linear regression
Основополагащ източник	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
Други названия	Bayesian weighted regression, BWLS, Bayesian heteroscedastic regression, weighted Bayesian linear regression	Bayesian linear regression, Bayesian normal regression, BLR, Bayesian least squares
Свързани	4	5
Резюме	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.