Documentation of 'cern.jet.random.tdouble.Empirical' Java class
Empirical
cern.jet.random.tdouble

Class Empirical

  • All Implemented Interfaces:
    DoubleFunction, IntFunction, java.io.Serializable, java.lang.Cloneable


    public class Empirical
    extends AbstractContinousDoubleDistribution
    Empirical distribution.

    The probability distribution function (pdf) must be provided by the user as an array of positive real numbers. The pdf does not need to be provided in the form of relative probabilities, absolute probabilities are also accepted.

    If interpolationType == LINEAR_INTERPOLATION a linear interpolation within the bin is computed, resulting in a constant density within each bin.

    If interpolationType == NO_INTERPOLATION no interpolation is performed and the result is a discrete distribution.

    Instance methods operate on a user supplied uniform random number generator; they are unsynchronized.

    Static methods operate on a default uniform random number generator; they are synchronized.

    Implementation: A uniform random number is generated using a user supplied generator. The uniform number is then transformed to the user's distribution using the cumulative probability distribution constructed from the pdf. The cumulative distribution is inverted using a binary search for the nearest bin boundary.

    This is a port of RandGeneral used in CLHEP 1.4.0 (C++).

    See Also:
    Serialized Form
    • Constructor Summary

      Constructors 
      Constructor and Description
      Empirical(double[] pdf, int interpolationType, DoubleRandomEngine randomGenerator)
      Constructs an Empirical distribution.
    • Method Summary

      All Methods Instance Methods Concrete Methods 
      Modifier and Type Method and Description
      double cdf(int k)
      Returns the cumulative distribution function.
      java.lang.Object clone()
      Returns a deep copy of the receiver; the copy will produce identical sequences.
      double nextDouble()
      Returns a random number from the distribution.
      double pdf(double x)
      Returns the probability distribution function.
      double pdf(int k)
      Returns the probability distribution function.
      void setState(double[] pdf, int interpolationType)
      Sets the distribution parameters.
      java.lang.String toString()
      Returns a String representation of the receiver.
      • Methods inherited from class java.lang.Object

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

      • Empirical

        public Empirical(double[] pdf,
                         int interpolationType,
                         DoubleRandomEngine randomGenerator)
        Constructs an Empirical distribution. The probability distribution function (pdf) is an array of positive real numbers. It need not be provided in the form of relative probabilities, absolute probabilities are also accepted. The pdf must satisfy both of the following conditions
        • 0.0 <= pdf[i] : 0<=i<=pdf.length-1
        • 0.0 < Sum(pdf[i]) : 0<=i<=pdf.length-1
        Parameters:
        pdf - the probability distribution function.
        interpolationType - can be either Empirical.NO_INTERPOLATION or Empirical.LINEAR_INTERPOLATION.
        randomGenerator - a uniform random number generator.
        Throws:
        java.lang.IllegalArgumentException - if at least one of the three conditions above is violated.
    • Method Detail

      • cdf

        public double cdf(int k)
        Returns the cumulative distribution function.
      • clone

        public java.lang.Object clone()
        Returns a deep copy of the receiver; the copy will produce identical sequences. After this call has returned, the copy and the receiver have equal but separate state.
        Overrides:
        clone in class AbstractDoubleDistribution
        Returns:
        a copy of the receiver.
      • pdf

        public double pdf(double x)
        Returns the probability distribution function.
      • pdf

        public double pdf(int k)
        Returns the probability distribution function.
      • setState

        public void setState(double[] pdf,
                             int interpolationType)
        Sets the distribution parameters. The pdf must satisfy both of the following conditions
        • 0.0 <= pdf[i] : 0 < =i <= pdf.length-1
        • 0.0 < Sum(pdf[i]) : 0 <=i <= pdf.length-1
        Parameters:
        pdf - probability distribution function.
        interpolationType - can be either Empirical.NO_INTERPOLATION or Empirical.LINEAR_INTERPOLATION.
        Throws:
        java.lang.IllegalArgumentException - if at least one of the three conditions above is violated.
      • toString

        public java.lang.String toString()
        Returns a String representation of the receiver.
        Overrides:
        toString in class java.lang.Object

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