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Outlier Detection Functions

Summary of Package Functions

  • detect_outliers_classic(df): Detect outliers in a time-series dataframe using Classical Seasonal Decomposition.
  • detect_outliers_today_classic(df): Detect outliers for the current date using Classical Seasonal Decomposition.
  • detect_outliers_latest_classic(df): Detect latest outliers using Classical Seasonal Decomposition.
  • detect_outliers_stl(df): Detect outliers using Seasonal-Trend Decomposition using LOESS (STL).
  • detect_outliers_today_stl(df): Detect outliers for the current date using STL.
  • detect_outliers_latest_stl(df): Detect latest outliers using STL.
  • detect_outliers_mstl(df): Detect outliers using Multiple Seasonal-Trend Decomposition using LOESS (MSTL).
  • detect_outliers_today_mstl(df): Detect outliers for the current date using MSTL.
  • detect_outliers_latest_mstl(df): Detect latest outliers using MSTL.
  • detect_outliers_esd(df): Detect outliers using the Generalized ESD or Seasonal ESD algorithm.
  • detect_outliers_today_esd(df): Detect outliers for the current date using ESD algorithm.
  • detect_outliers_latest_esd(df): Detect latest outliers using ESD algorithm.
  • detect_outliers_iqr(df): Detect outliers in a time-series dataframe when there's less than 2 years of data.
  • detect_outliers_moving_average(df): Detect outliers using Moving Average method.