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Regresija običnih najmanjih kvadrata (OLS)×Model vektorske korekcije pogrešaka (VECM)×
PodručjeEkonometrijaEkonometrija
ObiteljRegression modelRegression model
Godina nastanka20191987
TvoracWooldridge (textbook treatment); classical least squaresEngle & Granger
VrstaLinear regressionMultivariate time-series model
Temeljni izvorWooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860Engle, R. F. & Granger, C. W. J. (1987). Co-Integration and Error Correction: Representation, Estimation, and Testing. Econometrica, 55(2), 251-276. DOI ↗
Drugi naziviordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonuvector error correction model, error correction model, cointegration model, VECM (Vektör Hata Düzeltme Modeli)
Srodne54
SažetakOrdinary 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).The Vector Error Correction Model is a multivariate time-series model for cointegrated series that captures both their short-run dynamics and their long-run equilibrium relationship. It was introduced by Engle and Granger in 1987 as part of the cointegration and error-correction framework.
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ScholarGateUsporedite metode: OLS Regression · VECM. Preuzeto 2026-06-19 s https://scholargate.app/hr/compare