Package org.apache.commons.math3.distribution

Class UniformIntegerDistribution

java.lang.Object
org.apache.commons.math3.distribution.AbstractIntegerDistribution
org.apache.commons.math3.distribution.UniformIntegerDistribution
All Implemented Interfaces:
Serializable, IntegerDistribution
public class UniformIntegerDistribution extends AbstractIntegerDistribution
Implementation of the uniform integer distribution.
Since:
3.0
See Also:

  • Constructor Details

    • UniformIntegerDistribution

      public UniformIntegerDistribution(int lower, int upper) throws NumberIsTooLargeException
      Creates a new uniform integer distribution using the given lower and upper bounds (both inclusive).

      Note: this constructor will implicitly create an instance of Well19937c as random generator to be used for sampling only (see sample() and AbstractIntegerDistribution.sample(int)). In case no sampling is needed for the created distribution, it is advised to pass null as random generator via the appropriate constructors to avoid the additional initialisation overhead.

      Parameters:
      lower - Lower bound (inclusive) of this distribution.
      upper - Upper bound (inclusive) of this distribution.
      Throws:
      NumberIsTooLargeException - if lower >= upper.

    • UniformIntegerDistribution

      public UniformIntegerDistribution(RandomGenerator rng, int lower, int upper) throws NumberIsTooLargeException
      Creates a new uniform integer distribution using the given lower and upper bounds (both inclusive).
      Parameters:
      rng - Random number generator.
      lower - Lower bound (inclusive) of this distribution.
      upper - Upper bound (inclusive) of this distribution.
      Throws:
      NumberIsTooLargeException - if lower > upper.
      Since:
      3.1

  • Method Details

    • probability

      public 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

      public 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

    • getNumericalMean

      public double getNumericalMean()
      Use this method to get the numerical value of the mean of this distribution. For lower bound lower and upper bound upper, the mean is 0.5 * (lower + upper).
      Returns:
      the mean or Double.NaN if it is not defined

    • getNumericalVariance

      public double getNumericalVariance()
      Use this method to get the numerical value of the variance of this distribution. For lower bound lower and upper bound upper, and n = upper - lower + 1, the variance is (n^2 - 1) / 12.
      Returns:
      the variance (possibly Double.POSITIVE_INFINITY or Double.NaN if it is not defined)

    • getSupportLowerBound

      public 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}.

      The lower bound of the support is equal to the lower bound parameter of the distribution.
      Returns:
      lower bound of the support

    • getSupportUpperBound

      public 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}.

      The upper bound of the support is equal to the upper bound parameter of the distribution.
      Returns:
      upper bound of the support

    • isSupportConnected

      public 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. The support of this distribution is connected.
      Returns:
      true

    • sample

      public int sample()
      Generate a random value sampled from this distribution. The default implementation uses the inversion method.
      Specified by:
      sample in interface IntegerDistribution
      Overrides:
      sample in class AbstractIntegerDistribution
      Returns:
      a random value