class_docstr: Config class for `StatThreshold`.
class_docstr_tok: ["Config","class","for","`","StatThreshold","`","."]
docstr: :param target_seq_index (optional): The index of the univariate whose value we are considering thresholds of.
      If not provided, the model only works for univariate data.
docstr_tok: [":","param","target_seq_index","(","optional",")",":","The","index","of","the","univariate","whose","value","we","are","considering","thresholds","of",".","If","not","provided",",","the","model","only","works","for","univariate","data","."]
code: def __init__(self, target_seq_index: int = None, **kwargs):
      """
      :param target_seq_index (optional): The index of the univariate whose value we are considering thresholds of.
          If not provided, the model only works for univariate data.
      """
      super().__init__(**kwargs)
      self.target_seq_index = target_seq_index
  
file_path: merlion/merlion/models/anomaly/stat_threshold.py
imports: import pandas
  from merlion.models.base import NormalizingConfig
  from merlion.models.anomaly.base import DetectorConfig, DetectorBase
  from merlion.transform.moving_average import DifferenceTransform
label_desc: Use image node_id 1 to create a new StatThresholdConfig object from inherited base classes: DetectorConfig, NormalizingConfig with example: obj = StatThresholdConfig(target_seq_index)