So sánh phương pháp

	Hồi quy Tuyến tính Đơn giản Bayes	Bayesian Generalized Linear Model
Lĩnh vực	Thống kê	Thống kê
Họ	Regression model	Regression model
Năm ra đời	Early 19th century; textbook synthesis 2013	1989 (GLM); 1995 (Bayesian BDA)
Người khởi xướng	Laplace, P.-S. (early 19th c.); modern treatment: Gelman et al.	McCullagh & Nelder (GLM framework); Bayesian treatment formalized by Gelman et al.
Loại	Bayesian linear regression	Bayesian regression model
Công trình gốc	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
Tên gọi khác	Bayesian SLR, Bayesian univariate regression, probabilistic simple linear regression, Bayesian linear model	Bayesian GLM, Bayesian GLIM, Bayesian generalized linear regression, Bayes GLM
Liên quan	6	6
Tóm tắt	Bayesian Simple Linear Regression models the relationship between a continuous outcome and a single predictor by combining a Gaussian likelihood with prior distributions over the intercept, slope, and error variance. The result is a full posterior distribution over all parameters, providing probabilistic uncertainty quantification rather than a single point estimate.	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.