Package org.apache.commons.math3.distribution

Interface IntegerDistribution

All Known Implementing Classes:
AbstractIntegerDistribution, BinomialDistribution, EnumeratedIntegerDistribution, GeometricDistribution, HypergeometricDistribution, PascalDistribution, PoissonDistribution, UniformIntegerDistribution, ZipfDistribution
public interface IntegerDistribution
Interface for distributions on the integers.

  • Method Summary

    Modifier and Type
    Method
    Description
    double
    cumulativeProbability(int x)
    For a random variable X whose values are distributed according to this distribution, this method returns P(X <= x).
    double
    cumulativeProbability(int x0, int x1)
    For a random variable X whose values are distributed according to this distribution, this method returns P(x0 < X <= x1).
    double
    getNumericalMean()
    Use this method to get the numerical value of the mean of this distribution.
    double
    getNumericalVariance()
    Use this method to get the numerical value of the variance of this distribution.
    int
    getSupportLowerBound()
    Access the lower bound of the support.
    int
    getSupportUpperBound()
    Access the upper bound of the support.
    int
    inverseCumulativeProbability(double p)
    Computes the quantile function of this distribution.
    boolean
    isSupportConnected()
    Use this method to get information about whether the support is connected, i.e.
    double
    probability(int x)
    For a random variable X whose values are distributed according to this distribution, this method returns P(X = x).
    void
    reseedRandomGenerator(long seed)
    Reseed the random generator used to generate samples.
    int
    sample()
    Generate a random value sampled from this distribution.
    int[]
    sample(int sampleSize)
    Generate a random sample from the distribution.

  • Method Details

    • probability

      double probability(int x)
      For a random variable X whose values are distributed according to this distribution, this method returns P(X = x). In other words, this method represents the probability mass function (PMF) for the distribution.
      Parameters:
      x - the point at which the PMF is evaluated
      Returns:
      the value of the probability mass function at x

    • cumulativeProbability

      double cumulativeProbability(int x)
      For a random variable X whose values are distributed according to this distribution, this method returns P(X <= x). In other words, this method represents the (cumulative) distribution function (CDF) for this distribution.
      Parameters:
      x - the point at which the CDF is evaluated
      Returns:
      the probability that a random variable with this distribution takes a value less than or equal to x

    • cumulativeProbability

      double cumulativeProbability(int x0, int x1) throws NumberIsTooLargeException
      For a random variable X whose values are distributed according to this distribution, this method returns P(x0 < X <= x1).
      Parameters:
      x0 - the exclusive lower bound
      x1 - the inclusive upper bound
      Returns:
      the probability that a random variable with this distribution will take a value between x0 and x1, excluding the lower and including the upper endpoint
      Throws:
      NumberIsTooLargeException - if x0 > x1

    • inverseCumulativeProbability

      int inverseCumulativeProbability(double p) throws OutOfRangeException
      Computes the quantile function of this distribution. For a random variable X distributed according to this distribution, the returned value is
      • inf{x in Z | P(Xinvalid input: '<'=x) >= p} for 0 < p <= 1,
      • inf{x in Z | P(Xinvalid input: '<'=x) > 0} for p = 0.
      If the result exceeds the range of the data type int, then Integer.MIN_VALUE or Integer.MAX_VALUE is returned.
      Parameters:
      p - the cumulative probability
      Returns:
      the smallest p-quantile of this distribution (largest 0-quantile for p = 0)
      Throws:
      OutOfRangeException - if p < 0 or p > 1

    • getNumericalMean

      double getNumericalMean()
      Use this method to get the numerical value of the mean of this distribution.
      Returns:
      the mean or Double.NaN if it is not defined

    • getNumericalVariance

      double getNumericalVariance()
      Use this method to get the numerical value of the variance of this distribution.
      Returns:
      the variance (possibly Double.POSITIVE_INFINITY or Double.NaN if it is not defined)

    • getSupportLowerBound

      int getSupportLowerBound()
      Access the lower bound of the support. This method must return the same value as inverseCumulativeProbability(0). In other words, this method must return

      inf {x in Z | P(X invalid input: '<'= x) > 0}.

      Returns:
      lower bound of the support (Integer.MIN_VALUE for negative infinity)

    • getSupportUpperBound

      int getSupportUpperBound()
      Access the upper bound of the support. This method must return the same value as inverseCumulativeProbability(1). In other words, this method must return

      inf {x in R | P(X invalid input: '<'= x) = 1}.

      Returns:
      upper bound of the support (Integer.MAX_VALUE for positive infinity)

    • isSupportConnected

      boolean isSupportConnected()
      Use this method to get information about whether the support is connected, i.e. whether all integers between the lower and upper bound of the support are included in the support.
      Returns:
      whether the support is connected or not

    • reseedRandomGenerator

      void reseedRandomGenerator(long seed)
      Reseed the random generator used to generate samples.
      Parameters:
      seed - the new seed
      Since:
      3.0

    • sample

      int sample()
      Generate a random value sampled from this distribution.
      Returns:
      a random value
      Since:
      3.0

    • sample

      int[] sample(int sampleSize)
      Generate a random sample from the distribution.
      Parameters:
      sampleSize - the number of random values to generate
      Returns:
      an array representing the random sample
      Throws:
      NotStrictlyPositiveException - if sampleSize is not positive
      Since:
      3.0