Fixes

etna/analysis/outliers/confidence_interval_outliers.py

@@ -27,16 +27,16 @@ def get_anomalies_confidence_interval(
     Parameters
     ----------
     ts:
-        TSDataset with timeseries data(should contains all the necessary features)
+        TSDataset with timeseries data(should contains all the necessary features).
     model:
-        model for confidence interval estimation
+        Model for confidence interval estimation.
     interval_width:
-        width of the confidence interval
+       The significance level for the confidence interval. By default a 95% confidence interval is taken.
 
     Returns
     -------
     dict of outliers: Dict[str, List[pd.Timestamp]]
-        dict of outliers in format {segment: [outliers_timestamps]}
+        Dict of outliers in format {segment: [outliers_timestamps]}.
     """
     outliers_per_segment = {}
     time_points = np.array(ts.index.values)

etna/models/sarimax.py

@@ -6,12 +6,20 @@
 from typing import Union
 
 import pandas as pd
+from statsmodels.tools.sm_exceptions import ValueWarning
 from statsmodels.tsa.statespace.sarimax import SARIMAX
 
 from etna.datasets import TSDataset
 from etna.models.base import PerSegmentModel
 from etna.models.base import log_decorator
 
+warnings.filterwarnings(
+    message="No frequency information was provided, so inferred frequency .* will be used",
+    action="ignore",
+    category=ValueWarning,
+    module="statsmodels.tsa.base.tsa_model",
+)
+
 
 class _SARIMAXModel:
     """