'Test observations for outliers according to method
Parameters
method : str
- `bonferroni` : one-step correction
- `sidak` : one-step correction
- `holm-sidak` :
- `holm` :
- `simes-hochberg` :
- `hommel` :
- `fdr_bh` : Benjamini/Hochberg
- `fdr_by` : Benjamini/Yekutieli
See `statsmodels.stats.multitest.multipletests` for details.
alpha : float
familywise error rate
Returns
table : ndarray or DataFrame
Returns either an ndarray or a DataFrame if labels is not None.
Will attempt to get labels from model_results if available. The
columns are the Studentized residuals, the unadjusted p-value,
and the corrected p-value according to method.
Notes
The unadjusted p-value is stats.t.sf(abs(resid), df) where
df = df_resid - 1.'

def outlier_test(self, method='bonf', alpha=0.05):

    from statsmodels.stats.outliers_influence import outlier_test
    return outlier_test(self, method, alpha)
