Package org.apache.commons.math.random

Class 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.

    See Also:
    Serialized Form

    • Constructor Detail

      • 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 Detail

      • 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

      • getBinCount

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

      • 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