statsmodels.graphics.regressionplots.plot_leverage_resid2¶
-
statsmodels.graphics.regressionplots.
plot_leverage_resid2
(results, alpha=0.05, ax=None, **kwargs)[source]¶ Plots leverage statistics vs. normalized residuals squared
- Parameters
- results
results
instance
A regression results instance
- alpha
float
Specifies the cut-off for large-standardized residuals. Residuals are assumed to be distributed N(0, 1) with alpha=alpha.
- ax
Axes
instance
Matplotlib Axes instance
- results
- Returns
- fig
matplotlib
Figure
A matplotlib figure instance.
- fig
Examples
Using a model built from the the state crime dataset, plot the leverage statistics vs. normalized residuals squared. Observations with Large-standardized Residuals will be labeled in the plot.
>>> import statsmodels.api as sm >>> import matplotlib.pyplot as plt >>> import statsmodels.formula.api as smf
>>> crime_data = sm.datasets.statecrime.load_pandas() >>> results = smf.ols('murder ~ hs_grad + urban + poverty + single', ... data=crime_data.data).fit() >>> sm.graphics.plot_leverage_resid2(results) >>> plt.show()
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