Field Detail

• innerDistribution

  protected final EnumeratedDistribution<Integer> innerDistribution

  EnumeratedDistribution instance (using the Integer wrapper) used to generate the pmf.

Constructor Detail

• EnumeratedIntegerDistribution

  public EnumeratedIntegerDistribution(int[] singletons,
                               double[] probabilities)
                                throws DimensionMismatchException,
                                       NotPositiveException,
                                       MathArithmeticException,
                                       NotFiniteNumberException,
                                       NotANumberException

  Create a discrete distribution using the given probability mass function definition.

  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:

  singletons - array of random variable values.

  probabilities - array of probabilities.

  Throws:

  DimensionMismatchException - if singletons.length != probabilities.length

  NotPositiveException - if any of the probabilities are negative.

  NotFiniteNumberException - if any of the probabilities are infinite.

  NotANumberException - if any of the probabilities are NaN.

  MathArithmeticException - all of the probabilities are 0.

• EnumeratedIntegerDistribution

  public EnumeratedIntegerDistribution(RandomGenerator rng,
                               int[] singletons,
                               double[] probabilities)
                                throws DimensionMismatchException,
                                       NotPositiveException,
                                       MathArithmeticException,
                                       NotFiniteNumberException,
                                       NotANumberException

  Create a discrete distribution using the given random number generator and probability mass function definition.

  Parameters:

  rng - random number generator.

  singletons - array of random variable values.

  probabilities - array of probabilities.

  Throws:

  DimensionMismatchException - if singletons.length != probabilities.length

  NotPositiveException - if any of the probabilities are negative.

  NotFiniteNumberException - if any of the probabilities are infinite.

  NotANumberException - if any of the probabilities are NaN.

  MathArithmeticException - all of the probabilities are 0.

• EnumeratedIntegerDistribution

  public EnumeratedIntegerDistribution(RandomGenerator rng,
                               int[] data)

  Create a discrete integer-valued distribution from the input data. Values are assigned mass based on their frequency.

  Parameters:

  rng - random number generator used for sampling

  data - input dataset

  Since:

  3.6

• 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

  Since:

  3.6

Method Detail

• 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

• 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