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Examinează metodele selectate una lângă alta; rândurile care diferă sunt evidențiate.

Regresia prin metoda celor mai mici pătrate ordinare (OLS)×Factor de Inflație a Varianței (VIF)×
DomeniuEconometrieEconometrie
FamilieRegression modelRegression model
Anul apariției20191970
Autorul originalWooldridge (textbook treatment); classical least squaresDonald Marquardt
TipLinear regressionDiagnostic statistic
Sursa seminalăWooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860Marquardt, D. W. (1970). Generalized inverses, ridge regression, biased linear estimation, and nonlinear estimation. Technometrics, 12(3), 591–612. DOI ↗
Denumiri alternativeordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonuVIF, Variance Inflation Index, Multicollinearity Inflation Factor, Varyans Enflasyon Faktörü
Înrudite53
RezumatOrdinary 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 Variance Inflation Factor (VIF) is a scalar diagnostic statistic proposed by Donald Marquardt (1970) that quantifies how much the variance of an estimated regression coefficient increases due to linear dependence—multicollinearity—among the predictors in an ordinary least squares model. It is routinely applied in econometrics, social science, and biomedical research whenever analysts suspect that two or more independent variables move together closely enough to destabilize coefficient estimates.
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ScholarGateCompară metode: OLS Regression · Variance Inflation Factor. Preluat la 2026-06-18 de pe https://scholargate.app/ro/compare