Сравнение на методи

	Байесов метод на най-малките квадрати с тегла (Bayesian WLS)	Модел с Байесови фиксирани ефекти
Област	Иконометрия	Иконометрия
Семейство	Regression model	Regression model
Година на възникване	1971	2000–2008
Създател	Arnold Zellner (Bayesian econometrics framework)	Chib (2008); Lancaster (2000)
Тип	Bayesian weighted regression	Bayesian panel regression
Основополагащ източник	Zellner, A. (1971). An Introduction to Bayesian Inference in Econometrics. Wiley, New York. ISBN: 978-0471169376	Lancaster, T. (2000). The incidental parameter problem since 1948. Journal of Econometrics, 95(2), 391–413.
Други названия	Bayesian weighted regression, BWLS, Bayesian heteroscedastic regression, weighted Bayesian linear regression	Bayesian within estimator, Bayesian FE model, Bayesian individual fixed effects, Bayesian least squares dummy variable
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.	The Bayesian fixed effects model applies Bayesian inference to the classical within-group panel estimator. Unit-specific intercepts capture time-invariant unobserved heterogeneity, while prior distributions on all parameters allow probability statements about coefficients and full uncertainty quantification via the posterior distribution.