Linganisha mbinu

	OLS ya Kibayesiyani (Bayesian Ordinary Least Squares Regression)	Urejeshaji wa Njia ya Viwango Vidogo vya Kawaida (OLS)
Nyanja	Ekonometriki	Ekonometriki
Familia	Regression model	Regression model
Mwaka wa asili	1971	2019
Mwanzilishi	Arnold Zellner	Wooldridge (textbook treatment); classical least squares
Aina	Bayesian linear regression	Linear regression
Chanzo asilia	Zellner, A. (1971). An Introduction to Bayesian Inference in Econometrics. Wiley. ISBN: 978-0471169376	Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860
Majina mbadala	Bayesian linear regression, Bayesian normal regression, BLR, Bayesian least squares	ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu
Zinazohusiana	5	5
Muhtasari	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.	Ordinary Least Squares is the classical linear regression method that explains a continuous outcome as a linear combination of predictors. It estimates the coefficients by minimising the sum of squared residuals, and under the Gauss-Markov assumptions these estimates are the best linear unbiased estimator (BLUE).