Interface IntegerDistribution

All Superinterfaces:
DiscreteDistribution, Distribution
All Known Subinterfaces:
BinomialDistribution, HypergeometricDistribution, PascalDistribution, PoissonDistribution, ZipfDistribution
All Known Implementing Classes:
AbstractIntegerDistribution, BinomialDistributionImpl, HypergeometricDistributionImpl, PascalDistributionImpl, PoissonDistributionImpl, ZipfDistributionImpl

public interface IntegerDistribution extends DiscreteDistribution
Interface for discrete distributions of integer-valued random variables.
Version:
$Revision: 949535 $ $Date: 2010-05-30 19:00:15 +0200 (dim. 30 mai 2010) $
  • Method Summary

    Modifier and Type
    Method
    Description
    double
    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 this distribution, X, this method returns P(x0 ≤ X ≤ x1).
    int
    For this distribution, X, this method returns the largest x such that P(X ≤ x) <= p.
    double
    probability(int x)
    For a random variable X whose values are distributed according to this distribution, this method returns P(X = x).

    Methods inherited from interface org.apache.commons.math.distribution.DiscreteDistribution

    probability

    Methods inherited from interface org.apache.commons.math.distribution.Distribution

    cumulativeProbability, cumulativeProbability
  • 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 for the distribution.
      Parameters:
      x - the value at which the probability density function is evaluated.
      Returns:
      the value of the probability density function at x
    • cumulativeProbability

      double cumulativeProbability(int x) throws MathException
      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 distribution function, or PDF for the distribution.
      Parameters:
      x - the value at which the PDF is evaluated.
      Returns:
      PDF for this distribution.
      Throws:
      MathException - if the cumulative probability can not be computed due to convergence or other numerical errors.
    • cumulativeProbability

      double cumulativeProbability(int x0, int x1) throws MathException
      For this distribution, X, this method returns P(x0 ≤ X ≤ x1).
      Parameters:
      x0 - the inclusive, lower bound
      x1 - the inclusive, upper bound
      Returns:
      the cumulative probability.
      Throws:
      MathException - if the cumulative probability can not be computed due to convergence or other numerical errors.
      IllegalArgumentException - if x0 > x1
    • inverseCumulativeProbability

      int inverseCumulativeProbability(double p) throws MathException
      For this distribution, X, this method returns the largest x such that P(X ≤ x) <= p.

      Note that this definition implies:

      • If there is a minimum value, m, with positive probability under (the density of) X, then m - 1 is returned by inverseCumulativeProbability(0). If there is no such value m, Integer.MIN_VALUE is returned.
      • If there is a maximum value, M, such that P(X ≤ M) =1, then M is returned by inverseCumulativeProbability(1). If there is no such value, M, Integer.MAX_VALUE is returned.

      Parameters:
      p - the cumulative probability.
      Returns:
      the largest x such that P(X ≤ x) <= p
      Throws:
      MathException - if the inverse cumulative probability can not be computed due to convergence or other numerical errors.
      IllegalArgumentException - if p is not between 0 and 1 (inclusive)