statsmodels.stats.outliers_influence.variance_inflation_factor¶

statsmodels.stats.outliers_influence.variance_inflation_factor(exog, exog_idx, *, standardize=True)[source]¶

Variance inflation factor, VIF, for one exogenous variable

The variance inflation factor is a measure for the increase of the variance of the parameter estimates if an additional variable, given by exog_idx is added to the linear regression. It is a measure for multicollinearity of the design matrix, exog.

One recommendation is that if VIF is greater than 5, then the explanatory variable given by exog_idx is highly collinear with the other explanatory variables, and the parameter estimates will have large standard errors because of this.

Parameters:¶

exog{ndarray, DataFrame}: design matrix with all explanatory variables, as for example used in regression
exog_idxint: index of the exogenous variable in the columns of exog
standardizebool, optional: If True, standardizes the design matrix columns to mean 0 and standard deviation 1 before computing VIF. This ensures numerical stability for non-linear transformations or micro-scale data. Default is True.

Returns:¶

float: variance inflation factor