VIF is calculated for each predictor variable in a regression model. It is defined as:
VIF = 1 / (1 - R²)
Where R² is the coefficient of determination obtained by regressing the predictor variable against all other predictor variables. A high VIF indicates a high degree of multicollinearity.
