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statsmodels.stats.outliers_influence.variance_inflation_factor

statsmodels.stats.outliers_influence.variance_inflation_factor(exog, exog_idx)[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, (nobs, k_vars)

design matrix with all explanatory variables, as for example used in regression

exog_idx : int

index of the exogenous variable in the columns of exog

Returns:

vif : float

variance inflation factor

See also

xxx
class for regression diagnostics TODO: doesn’t exist yet

Notes

This function does not save the auxiliary regression.

References

http://en.wikipedia.org/wiki/Variance_inflation_factor

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