Interface RealDistribution

All Known Implementing Classes:
AbstractRealDistribution, BetaDistribution, CauchyDistribution, ChiSquaredDistribution, ConstantRealDistribution, EmpiricalDistribution, EnumeratedRealDistribution, ExponentialDistribution, FDistribution, GammaDistribution, GumbelDistribution, LaplaceDistribution, LevyDistribution, LogisticDistribution, LogNormalDistribution, NakagamiDistribution, NormalDistribution, ParetoDistribution, TDistribution, TriangularDistribution, UniformRealDistribution, WeibullDistribution

public interface RealDistribution
Base interface for distributions on the reals.
Since:
3.0
  • 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(double x0, double x1)
    Deprecated.
    As of 3.1.
    double
    density(double x)
    Returns the probability density function (PDF) of this distribution evaluated at the specified point x.
    double
    Use this method to get the numerical value of the mean of this distribution.
    double
    Use this method to get the numerical value of the variance of this distribution.
    double
    Access the lower bound of the support.
    double
    Access the upper bound of the support.
    double
    Computes the quantile function of this distribution.
    boolean
    Use this method to get information about whether the support is connected, i.e.
    boolean
    Deprecated.
    to be removed in 4.0
    boolean
    Deprecated.
    to be removed in 4.0
    double
    probability(double x)
    For a random variable X whose values are distributed according to this distribution, this method returns P(X = x).
    void
    Reseed the random generator used to generate samples.
    double
    Generate a random value sampled from this distribution.
    double[]
    sample(int sampleSize)
    Generate a random sample from the distribution.
  • Method Details

    • probability

      double probability(double 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 point x
    • density

      double density(double x)
      Returns the probability density function (PDF) of this distribution evaluated at the specified point x. In general, the PDF is the derivative of the CDF. If the derivative does not exist at x, then an appropriate replacement should be returned, e.g. Double.POSITIVE_INFINITY, Double.NaN, or the limit inferior or limit superior of the difference quotient.
      Parameters:
      x - the point at which the PDF is evaluated
      Returns:
      the value of the probability density function at point x
    • cumulativeProbability

      double cumulativeProbability(double 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
    • cumulativeProbability

      @Deprecated double cumulativeProbability(double x0, double x1) throws NumberIsTooLargeException
      Deprecated.
      As of 3.1. In 4.0, this method will be renamed probability(double x0, double x1).
      For a random variable X whose values are distributed according to this distribution, this method returns P(x0 < X <= x1).
      Parameters:
      x0 - the exclusive lower bound
      x1 - the inclusive upper bound
      Returns:
      the probability that a random variable with this distribution takes a value between x0 and x1, excluding the lower and including the upper endpoint
      Throws:
      NumberIsTooLargeException - if x0 > x1
    • inverseCumulativeProbability

      double inverseCumulativeProbability(double p) throws OutOfRangeException
      Computes the quantile function of this distribution. For a random variable X distributed according to this distribution, the returned value is
      • inf{x in R | P(Xinvalid input: '<'=x) >= p} for 0 < p <= 1,
      • inf{x in R | P(Xinvalid input: '<'=x) > 0} for p = 0.
      Parameters:
      p - the cumulative probability
      Returns:
      the smallest p-quantile of this distribution (largest 0-quantile for p = 0)
      Throws:
      OutOfRangeException - if p < 0 or p > 1
    • getNumericalMean

      double getNumericalMean()
      Use this method to get the numerical value of the mean of this distribution.
      Returns:
      the mean or Double.NaN if it is not defined
    • getNumericalVariance

      double getNumericalVariance()
      Use this method to get the numerical value of the variance of this distribution.
      Returns:
      the variance (possibly Double.POSITIVE_INFINITY as for certain cases in TDistribution) or Double.NaN if it is not defined
    • getSupportLowerBound

      double 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 R | P(X invalid input: '<'= x) > 0}.

      Returns:
      lower bound of the support (might be Double.NEGATIVE_INFINITY)
    • getSupportUpperBound

      double 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}.

      Returns:
      upper bound of the support (might be Double.POSITIVE_INFINITY)
    • isSupportLowerBoundInclusive

      @Deprecated boolean isSupportLowerBoundInclusive()
      Deprecated.
      to be removed in 4.0
      Whether or not the lower bound of support is in the domain of the density function. Returns true iff getSupporLowerBound() is finite and density(getSupportLowerBound()) returns a non-NaN, non-infinite value.
      Returns:
      true if the lower bound of support is finite and the density function returns a non-NaN, non-infinite value there
    • isSupportUpperBoundInclusive

      @Deprecated boolean isSupportUpperBoundInclusive()
      Deprecated.
      to be removed in 4.0
      Whether or not the upper bound of support is in the domain of the density function. Returns true iff getSupportUpperBound() is finite and density(getSupportUpperBound()) returns a non-NaN, non-infinite value.
      Returns:
      true if the upper bound of support is finite and the density function returns a non-NaN, non-infinite value there
    • isSupportConnected

      boolean isSupportConnected()
      Use this method to get information about whether the support is connected, i.e. whether all values between the lower and upper bound of the support are included in the support.
      Returns:
      whether the support is connected or not
    • reseedRandomGenerator

      void reseedRandomGenerator(long seed)
      Reseed the random generator used to generate samples.
      Parameters:
      seed - the new seed
    • sample

      double sample()
      Generate a random value sampled from this distribution.
      Returns:
      a random value.
    • sample

      double[] sample(int sampleSize)
      Generate a random sample from the distribution.
      Parameters:
      sampleSize - the number of random values to generate
      Returns:
      an array representing the random sample
      Throws:
      NotStrictlyPositiveException - if sampleSize is not positive