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Regresi Kuasa Dua Terkecil Biasa (OLS)×Model Pembetulan Ralat Vektor (VECM)×
BidangEkonometrikEkonometrik
KeluargaRegression modelRegression model
Tahun asal20191987
PengasasWooldridge (textbook treatment); classical least squaresEngle & Granger
JenisLinear regressionMultivariate time-series model
Sumber perintisWooldridge, 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 ↗
Aliasordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonuvector error correction model, error correction model, cointegration model, VECM (Vektör Hata Düzeltme Modeli)
Berkaitan54
RingkasanOrdinary 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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ScholarGateBandingkan kaedah: OLS Regression · VECM. Dicapai 2026-06-19 daripada https://scholargate.app/ms/compare