Documentation of 'org.ddogleg.fitting.modelset.distance.FitByMedianStatistics' Java class
FitByMedianStatistics
org.ddogleg.fitting.modelset.distance

Class FitByMedianStatistics<Model,Point>

  • All Implemented Interfaces:
    StatisticalFit<Model,Point>


    public class FitByMedianStatistics<Model,Point>
    extends java.lang.Object
    implements StatisticalFit<Model,Point>
    Computes the median error and prunes points if they have more than the specified percentile error.
    • Constructor Summary

      Constructors 
      Constructor and Description
      FitByMedianStatistics(double pruneThreshold)
      Creates a new FitByMedianStatistics.
    • Method Summary

      All Methods Instance Methods Concrete Methods 
      Modifier and Type Method and Description
      void computeStatistics()
      Computes the statistic error of the model to the data points.
      double getErrorMetric()
      Returns the computed statistical error.
      void init(DistanceFromModel<Model,Point> modelError, java.util.LinkedList<PointIndex<Point>> allPoints)
      This is called once to provide access to internal data structures of the owner.
      void prune()
      Removes all samples which have an error larger than the specified percentile error.
      • Methods inherited from class java.lang.Object

        equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
    • Constructor Detail

      • FitByMedianStatistics

        public FitByMedianStatistics(double pruneThreshold)
        Creates a new FitByMedianStatistics.
        Parameters:
        pruneThreshold - Fraction of samples that are not pruned.
    • Method Detail

      • init

        public void init(DistanceFromModel<Model,Point> modelError,
                         java.util.LinkedList<PointIndex<Point>> allPoints)
        Description copied from interface: StatisticalFit
        This is called once to provide access to internal data structures of the owner.
        Specified by:
        init in interface StatisticalFit<Model,Point>
        Parameters:
        modelError - Computes the error between a point and the model
        allPoints - Contains all the points which are currently considered part of the model.
      • prune

        public void prune()
        Removes all samples which have an error larger than the specified percentile error.
        Specified by:
        prune in interface StatisticalFit<Model,Point>

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