statsmodels.graphics.regressionplots.influence_plot(results, external=True, alpha=0.05, criterion='cooks', size=48, plot_alpha=0.75, ax=None, **kwargs)
Plot of influence in regression. Plots studentized resids vs. leverage.
fig – The matplotlib figure that contains the Axes.
Row labels for the observations in which the leverage, measured by the diagonal of the hat matrix, is high or the residuals are large, as the combination of large residuals and a high influence value indicates an influence point. The value of large residuals can be controlled using the
alpha parameter. Large leverage points are identified as hat_i > 2 * (df_model + 1)/nobs.
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© 2006–2008 Scipy Developers
© 2006 Jonathan E. Taylor
Licensed under the 3-clause BSD License.