Class EmpiricalDistributionImpl

java.lang.Object
org.apache.commons.math.random.EmpiricalDistributionImpl
All Implemented Interfaces:
Serializable, EmpiricalDistribution

public class EmpiricalDistributionImpl extends Object implements Serializable, EmpiricalDistribution
Implements EmpiricalDistribution interface. This implementation uses what amounts to the Variable Kernel Method with Gaussian smoothing:

Digesting the input file

  1. Pass the file once to compute min and max.
  2. Divide the range from min-max into binCount "bins."
  3. Pass the data file again, computing bin counts and univariate statistics (mean, std dev.) for each of the bins
  4. Divide the interval (0,1) into subintervals associated with the bins, with the length of a bin's subinterval proportional to its count.
Generating random values from the distribution
  1. Generate a uniformly distributed value in (0,1)
  2. Select the subinterval to which the value belongs.
  3. Generate a random Gaussian value with mean = mean of the associated bin and std dev = std dev of associated bin.

USAGE NOTES:

  • The binCount is set by default to 1000. A good rule of thumb is to set the bin count to approximately the length of the input file divided by 10.
  • The input file must be a plain text file containing one valid numeric entry per line.

Version:
$Revision: 1003886 $ $Date: 2010-10-02 23:04:44 +0200 (sam. 02 oct. 2010) $
See Also:
  • Constructor Details

    • EmpiricalDistributionImpl

      public EmpiricalDistributionImpl()
      Creates a new EmpiricalDistribution with the default bin count.
    • EmpiricalDistributionImpl

      public EmpiricalDistributionImpl(int binCount)
      Creates a new EmpiricalDistribution with the specified bin count.
      Parameters:
      binCount - number of bins
  • Method Details

    • load

      public void load(double[] in)
      Computes the empirical distribution from the provided array of numbers.
      Specified by:
      load in interface EmpiricalDistribution
      Parameters:
      in - the input data array
    • load

      public void load(URL url) throws IOException
      Computes the empirical distribution using data read from a URL.
      Specified by:
      load in interface EmpiricalDistribution
      Parameters:
      url - url of the input file
      Throws:
      IOException - if an IO error occurs
    • load

      public void load(File file) throws IOException
      Computes the empirical distribution from the input file.
      Specified by:
      load in interface EmpiricalDistribution
      Parameters:
      file - the input file
      Throws:
      IOException - if an IO error occurs
    • getNextValue

      public double getNextValue() throws IllegalStateException
      Generates a random value from this distribution.
      Specified by:
      getNextValue in interface EmpiricalDistribution
      Returns:
      the random value.
      Throws:
      IllegalStateException - if the distribution has not been loaded
    • getSampleStats

      public StatisticalSummary getSampleStats()
      Returns a StatisticalSummary describing this distribution. Preconditions:
      • the distribution must be loaded before invoking this method
      Specified by:
      getSampleStats in interface EmpiricalDistribution
      Returns:
      the sample statistics
      Throws:
      IllegalStateException - if the distribution has not been loaded
    • getBinCount

      public int getBinCount()
      Returns the number of bins.
      Specified by:
      getBinCount in interface EmpiricalDistribution
      Returns:
      the number of bins.
    • getBinStats

      public List<SummaryStatistics> getBinStats()
      Returns a List of SummaryStatistics instances containing statistics describing the values in each of the bins. The list is indexed on the bin number.
      Specified by:
      getBinStats in interface EmpiricalDistribution
      Returns:
      List of bin statistics.
    • getUpperBounds

      public double[] getUpperBounds()

      Returns a fresh copy of the array of upper bounds for the bins. Bins are:
      [min,upperBounds[0]],(upperBounds[0],upperBounds[1]],..., (upperBounds[binCount-2], upperBounds[binCount-1] = max].

      Note: In versions 1.0-2.0 of commons-math, this method incorrectly returned the array of probability generator upper bounds now returned by getGeneratorUpperBounds().

      Specified by:
      getUpperBounds in interface EmpiricalDistribution
      Returns:
      array of bin upper bounds
      Since:
      2.1
    • getGeneratorUpperBounds

      public double[] getGeneratorUpperBounds()

      Returns a fresh copy of the array of upper bounds of the subintervals of [0,1] used in generating data from the empirical distribution. Subintervals correspond to bins with lengths proportional to bin counts.

      In versions 1.0-2.0 of commons-math, this array was (incorrectly) returned by getUpperBounds().

      Returns:
      array of upper bounds of subintervals used in data generation
      Since:
      2.1
    • isLoaded

      public boolean isLoaded()
      Property indicating whether or not the distribution has been loaded.
      Specified by:
      isLoaded in interface EmpiricalDistribution
      Returns:
      true if the distribution has been loaded