Constructor Detail

• ZipfDistribution

  public ZipfDistribution(int numberOfElements,
                  double exponent)

  Create a new Zipf distribution with the given number of elements and exponent.

  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:

  numberOfElements - Number of elements.

  exponent - Exponent.

  Throws:

  NotStrictlyPositiveException - if numberOfElements <= 0 or exponent <= 0.

• ZipfDistribution

  public ZipfDistribution(RandomGenerator rng,
                  int numberOfElements,
                  double exponent)
                   throws NotStrictlyPositiveException

  Creates a Zipf distribution.

  Parameters:

  rng - Random number generator.

  numberOfElements - Number of elements.

  exponent - Exponent.

  Throws:

  NotStrictlyPositiveException - if numberOfElements <= 0 or exponent <= 0.

  Since:

  3.1

Method Detail

• getNumberOfElements

  public int getNumberOfElements()

  Get the number of elements (e.g. corpus size) for the distribution.

  Returns:

  the number of elements

• getExponent

  public double getExponent()

  Get the exponent characterizing the distribution.

  Returns:

  the exponent

• 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

• logProbability

  public double logProbability(int x)

  For a random variable X whose values are distributed according to this distribution, this method returns log(P(X = x)), where log is the natural logarithm. In other words, this method represents the logarithm of the probability mass function (PMF) for the distribution. Note that due to the floating point precision and under/overflow issues, this method will for some distributions be more precise and faster than computing the logarithm of IntegerDistribution.probability(int).

  The default implementation simply computes the logarithm of probability(x).

  Overrides:

  logProbability in class AbstractIntegerDistribution

  Parameters:

  x - the point at which the PMF is evaluated

  Returns:

  the logarithm of 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 number of elements N and exponent s, the mean is Hs1 / Hs, where

  • Hs1 = generalizedHarmonic(N, s - 1),
  • Hs = generalizedHarmonic(N, s).

  Returns:

  the mean or Double.NaN if it is not defined

• calculateNumericalMean

  protected double calculateNumericalMean()

  Used by getNumericalMean().

  Returns:

  the mean of this distribution

• getNumericalVariance

  public double getNumericalVariance()

  Use this method to get the numerical value of the variance of this distribution. For number of elements N and exponent s, the mean is (Hs2 / Hs) - (Hs1^2 / Hs^2), where

  • Hs2 = generalizedHarmonic(N, s - 2),
  • Hs1 = generalizedHarmonic(N, s - 1),
  • Hs = generalizedHarmonic(N, s).

  Returns:

  the variance (possibly Double.POSITIVE_INFINITY or Double.NaN if it is not defined)

• calculateNumericalVariance

  protected double calculateNumericalVariance()

  Used by getNumericalVariance().

  Returns:

  the variance of this distribution

• 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}.

  The lower bound of the support is always 1 no matter the parameters.

  Returns:

  lower bound of the support (always 1)

• 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}.

  The upper bound of the support is the number of elements.

  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