Krahasoni metodat

	Modeli i Përgjithësuar Linear Bayesiani	Regresioni Multilinear Bayesiano
Fusha	Statistikë	Statistikë
Familja	Regression model	Regression model
Viti i origjinës	1989 (GLM); 1995 (Bayesian BDA)	1971
Krijuesi	McCullagh & Nelder (GLM framework); Bayesian treatment formalized by Gelman et al.	Arnold Zellner (econometric formulation); broader development by Harold Jeffreys and Gelman et al.
Lloji	Bayesian regression model	Bayesian parametric regression
Burimi themelues	Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A., & Rubin, D. B. (2013). Bayesian Data Analysis (3rd ed.). CRC Press. ISBN: 978-1439840955	Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A., & Rubin, D. B. (2013). Bayesian Data Analysis (3rd ed.). CRC Press. ISBN: 978-1439840955
Emërtime të tjera	Bayesian GLM, Bayesian GLIM, Bayesian generalized linear regression, Bayes GLM	Bayesian MLR, Bayesian linear regression, Bayesian multivariate regression, conjugate normal-inverse-gamma regression
Të lidhura	6	6
Përmbledhja	A Bayesian Generalized Linear Model (Bayesian GLM) extends the classical GLM framework by placing prior distributions on the regression coefficients and updating them with data via Bayes' theorem. This yields a full posterior distribution over parameters rather than single point estimates, enabling richer uncertainty quantification and principled incorporation of prior knowledge for any exponential-family outcome.	Bayesian Multiple Linear Regression models a continuous outcome as a linear combination of several predictors, but instead of producing a single point estimate it yields a full posterior distribution over all regression coefficients and the error variance. This makes uncertainty quantification explicit and allows seamlessly incorporating prior knowledge from theory or previous studies.