statsmodels.regression.linear_model.OLSResults.outlier_test¶
method
-
OLSResults.
outlier_test
(method='bonf', alpha=0.05, labels=None, order=False, cutoff=None)[source]¶ 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
labels : None or array_like
If labels is not None, then it will be used as index to the returned pandas DataFrame. See also Returns below
order : bool
Whether or not to order the results by the absolute value of the studentized residuals. If labels are provided they will also be sorted.
cutoff : None or float in [0, 1]
If cutoff is not None, then the return only includes observations with multiple testing corrected p-values strictly below the cutoff. The returned array or dataframe can be empty if t
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.