ScholarGate
Assistent

Methoden vergelijken

Bekijk de geselecteerde methoden naast elkaar; rijen die verschillen zijn gemarkeerd.

Gewone Kleinste Kwadraten (GKK) Regressie×Variantie-inflatiefactor (VIF)×
VakgebiedEconometrieEconometrie
FamilieRegression modelRegression model
Jaar van ontstaan20191970
GrondleggerWooldridge (textbook treatment); classical least squaresDonald Marquardt
TypeLinear regressionDiagnostic statistic
Oorspronkelijke bronWooldridge, 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 ↗
Aliassenordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonuVIF, Variance Inflation Index, Multicollinearity Inflation Factor, Varyans Enflasyon Faktörü
Verwant53
SamenvattingOrdinary 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.
ScholarGateGegevensset
  1. v1
  2. 1 Bronnen
  3. PUBLISHED
  1. v1
  2. 1 Bronnen
  3. PUBLISHED

Naar zoeken Dia's downloaden

ScholarGateMethoden vergelijken: OLS Regression · Variance Inflation Factor. Geraadpleegd op 2026-06-18 via https://scholargate.app/nl/compare