手法を比較

	分散拡大係数（VIF）	最小二乗法 (OLS) 回帰
分野	計量経済学	計量経済学
系統	Regression model	Regression model
提唱年	1970	2019
提唱者	Donald Marquardt	Wooldridge (textbook treatment); classical least squares
種類	Diagnostic statistic	Linear regression
原典	Marquardt, D. W. (1970). Generalized inverses, ridge regression, biased linear estimation, and nonlinear estimation. Technometrics, 12(3), 591–612.	Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860
別名	VIF, Variance Inflation Index, Multicollinearity Inflation Factor, Varyans Enflasyon Faktörü	ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu
関連	3	5
概要	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.	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).