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Naizgled nepovezane regresije (SUR)×Regresija običnih najmanjih kvadrata (OLS)×
PodručjeEkonometrijaEkonometrija
ObiteljRegression modelRegression model
Godina nastanka19622019
TvoracArnold ZellnerWooldridge (textbook treatment); classical least squares
VrstaSystem regression (multi-equation)Linear regression
Temeljni izvorZellner, 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. DOI ↗Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860
Drugi naziviSUR, Zellner's SUR, seemingly unrelated regression equations, Görünürde İlişkisiz Regresyon (SUR)ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu
Srodne55
SažetakSeemingly 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).
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ScholarGateUsporedite metode: Seemingly Unrelated Regression · OLS Regression. Preuzeto 2026-06-18 s https://scholargate.app/hr/compare