Class EnumeratedIntegerDistribution

java.lang.Object
org.hipparchus.distribution.discrete.AbstractIntegerDistribution
org.hipparchus.distribution.discrete.EnumeratedIntegerDistribution
All Implemented Interfaces:
Serializable, IntegerDistribution

public class EnumeratedIntegerDistribution extends AbstractIntegerDistribution
Implementation of an integer-valued EnumeratedDistribution.

Values with zero-probability are allowed but they do not extend the support.

Duplicate values are allowed. Probabilities of duplicate values are combined when computing cumulative probabilities and statistics.

See Also:
  • Constructor Details

    • EnumeratedIntegerDistribution

      public EnumeratedIntegerDistribution(int[] singletons, double[] probabilities) throws MathIllegalArgumentException
      Create a discrete distribution using the given probability mass function definition.
      Parameters:
      singletons - array of random variable values.
      probabilities - array of probabilities.
      Throws:
      MathIllegalArgumentException - if singletons.length != probabilities.length
      MathIllegalArgumentException - if probabilities contains negative, infinite or NaN values or only 0's
    • EnumeratedIntegerDistribution

      public EnumeratedIntegerDistribution(int[] data)
      Create a discrete integer-valued distribution from the input data. Values are assigned mass based on their frequency. For example, [0,1,1,2] as input creates a distribution with values 0, 1 and 2 having probability masses 0.25, 0.5 and 0.25 respectively,
      Parameters:
      data - input dataset
  • 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.
      Returns:
      sum(singletons[i] * probabilities[i])
    • getNumericalVariance

      public double getNumericalVariance()
      Use this method to get the numerical value of the variance of this distribution.
      Returns:
      sum((singletons[i] - mean) ^ 2 * probabilities[i])
    • 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 <= x) > 0}.

      Returns the lowest value with non-zero probability.
      Returns:
      the lowest value with non-zero probability.
    • 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 <= x) = 1}.

      Returns the highest value with non-zero probability.
      Returns:
      the highest value with non-zero probability.
    • 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
    • getPmf

      public List<Pair<Integer,Double>> getPmf()
      Return the probability mass function as a list of (value, probability) pairs.
      Returns:
      the probability mass function.