Package elki.timeseries

Class OfflineChangePointDetectionAlgorithm

  • All Implemented Interfaces:
    elki.Algorithm
    @Title("Off-line Change Point Detection")
@Description("Detects multiple change points in a time series")
@Reference(authors="D. Picard",title="Testing and Estimating Change-Points in Time Series ",booktitle="Advances in Applied Probability Vol. 17",url="https://doi.org/10.2307/1427090",bibkey="doi:10.2307/1427090") @Reference(authors="E. S. Page",title="On Problems in which a Change in a Parameter Occurs at an Unknown Point",booktitle="Biometrika Vol. 44",url="https://doi.org/10.2307/2333258",bibkey="doi:10.2307/2333258") @Reference(authors="M. Basseville, I. V. Nikiforov",title="Section 2.6: Off-line Change Detection",booktitle="Detection of Abrupt Changes - Theory and Application",url="http://people.irisa.fr/Michele.Basseville/kniga/kniga.pdf",bibkey="books/prentice/BassevilleN93/C2")
public class OfflineChangePointDetectionAlgorithm
extends java.lang.Object
implements elki.Algorithm
    Off-line change point detection algorithm detecting a change in mean, based on the cumulative sum (CUSUM), same-variance assumption, and using bootstrap sampling for significance estimation.

    References:

    D. Picard
    Testing and Estimating Change-Points in Time Series
    Advances in Applied Probability Vol. 17

    early results along these lines can be found in:

    E. S. Page
    On Problems in which a Change in a Parameter Occurs at an Unknown Point
    Biometrika Vol. 44

    also discussed in:

    M. Basseville and I. V. Nikiforov
    Section 2.6: Off-line Change Detection
    Detection of Abrupt Changes - Theory and Application

    Since:
    0.7.5
    Author:
    Sebastian Rühl, Erich Schubert

    • Field Summary

      Fields 
      Modifier and Type Field Description
      (package private) int bootstrapSamples
      Number of samples for bootstrap significance.
      (package private) double minConfidence
      Mininum confidence.
      (package private) elki.utilities.random.RandomFactory rnd
      Random generator

    • Constructor Summary

      Constructors 
      Constructor Description
      OfflineChangePointDetectionAlgorithm​(double confidence, int bootstrapSteps, elki.utilities.random.RandomFactory rnd)
      Constructor

    • Method Summary

      All Methods Static Methods Instance Methods Concrete Methods 
      Modifier and Type Method Description
      static elki.utilities.pairs.DoubleIntPair bestChangeInMean​(double[] sums, int begin, int end)
      Find the best position to assume a change in mean.
      static void cusum​(double[] data, double[] out, int begin, int end)
      Compute the incremental sum of an array, i.e. the sum of all points up to the given index.
      elki.data.type.TypeInformation[] getInputTypeRestriction()  
      ChangePoints run​(elki.database.relation.Relation<elki.data.DoubleVector> relation)
      Executes multiple change point detection for given relation
      static void shuffle​(double[] bstrap, int len, java.util.Random rnd)
      Fisher-Yates shuffle of a partial array

      • Methods inherited from class java.lang.Object

        clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

      • Methods inherited from interface elki.Algorithm

        autorun

    • Field Detail

      • bootstrapSamples

        int bootstrapSamples
        Number of samples for bootstrap significance.

      • minConfidence

        double minConfidence
        Mininum confidence.

      • rnd

        elki.utilities.random.RandomFactory rnd
        Random generator

    • Constructor Detail

      • OfflineChangePointDetectionAlgorithm

        public OfflineChangePointDetectionAlgorithm​(double confidence,
                                            int bootstrapSteps,
                                            elki.utilities.random.RandomFactory rnd)
        Constructor
        Parameters:
        confidence - Confidence
        bootstrapSteps - Steps for bootstrapping

    • Method Detail

      • getInputTypeRestriction

        public elki.data.type.TypeInformation[] getInputTypeRestriction()
        Specified by:
        getInputTypeRestriction in interface elki.Algorithm

      • run

        public ChangePoints run​(elki.database.relation.Relation<elki.data.DoubleVector> relation)
        Executes multiple change point detection for given relation
        Parameters:
        relation - the relation to process
        Returns:
        list with all the detected change point for every time series

      • cusum

        public static void cusum​(double[] data,
                         double[] out,
                         int begin,
                         int end)
        Compute the incremental sum of an array, i.e. the sum of all points up to the given index.
        Parameters:
        data - Input data
        out - Output array (must be large enough).

      • bestChangeInMean

        public static elki.utilities.pairs.DoubleIntPair bestChangeInMean​(double[] sums,
                                                                  int begin,
                                                                  int end)
        Find the best position to assume a change in mean.
        Parameters:
        sums - Cumulative sums
        begin - Interval begin
        end - Interval end
        Returns:
        Best change position

      • shuffle

        public static void shuffle​(double[] bstrap,
                           int len,
                           java.util.Random rnd)
        Fisher-Yates shuffle of a partial array
        Parameters:
        bstrap - Data to shuffle
        len - Length of valid data
        rnd - Random generator