Variance Inflation Factor In R

Variance Inflation Factor In R. I is the predictor youre looking at eg. If VIF is more than 10 multicolinearity is strongly suggested.

Why Multicollinearity Is A Problem And How To Detect It In Your Regression Models By Kan Nishida Learn Data Science from blog.exploratory.io

To evaluate multicolinearity of multiple regression model calculating the variance inflation factor VIF from the result of lm. The Variance Inflation Factor VIF is a measure of colinearity among predictor variables within a multiple regression. K_vars exogshape1 x_i exog exog_idx mask nparangek_vars exog_idx x_noti exog mask r_squared_i OLSx_i x_notifitrsquared.

According to the help file this latter value.

Mathematically the VIF for a regression model variable is equal to the. The VIF of a predictor is a measure for how easily it is predicted from a linear. A common R function used for testing regression assumptions and specifically multicolinearity is VIF. This would mean that the other predictors explain 99 of the variation in the given predictor.