विधियों की तुलना करें

	प्रतीत होने वाली असंबंधित रिग्रेशन (SUR)	साधारण न्यूनतम वर्ग (OLS) समाश्रयण
क्षेत्र	अर्थमिति	अर्थमिति
परिवार	Regression model	Regression model
उद्भव वर्ष	1962	2019
प्रवर्तक	Arnold Zellner	Wooldridge (textbook treatment); classical least squares
प्रकार	System regression (multi-equation)	Linear regression
मौलिक स्रोत	Zellner, A. (1962). An Efficient Method of Estimating Seemingly Unrelated Regressions and Tests for Aggregation Bias. Journal of the American Statistical Association, 57(298), 348-368.	Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860
उपनाम	SUR, Zellner's SUR, seemingly unrelated regression equations, Görünürde İlişkisiz Regresyon (SUR)	ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu
संबंधित	5	5
सारांश	Seemingly Unrelated Regressions, introduced by Arnold Zellner in 1962, is a system regression method that estimates several linear equations jointly when their error terms are correlated across equations. By exploiting that cross-equation correlation through generalized least squares, it is more efficient than estimating each equation separately by OLS.	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).