Package org.hipparchus.distribution

Interface MultivariateRealDistribution

All Known Implementing Classes:
AbstractMultivariateRealDistribution, MixtureMultivariateNormalDistribution, MixtureMultivariateRealDistribution, MultivariateNormalDistribution
public interface MultivariateRealDistribution
Base interface for multivariate continuous distributions.

This is based largely on the RealDistribution interface, but cumulative distribution functions are not required because they are often quite difficult to compute for multivariate distributions.

  • Method Summary

    Modifier and Type
    Method
    Description
    double
    density(double[] x)
    Returns the probability density function (PDF) of this distribution evaluated at the specified point x.
    int
    getDimension()
    Gets the number of random variables of the distribution.
    void
    reseedRandomGenerator(long seed)
    Reseeds the random generator used to generate samples.
    double[]
    sample()
    Generates a random value vector sampled from this distribution.
    double[][]
    sample(int sampleSize)
    Generates a list of a random value vectors from the distribution.

  • Method Details

    • 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 cumulative distribution function. 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 - Point at which the PDF is evaluated.
      Returns:
      the value of the probability density function at point x.

    • reseedRandomGenerator

      void reseedRandomGenerator(long seed)
      Reseeds the random generator used to generate samples.
      Parameters:
      seed - Seed with which to initialize the random number generator.

    • getDimension

      int getDimension()
      Gets the number of random variables of the distribution. It is the size of the array returned by the sample method.
      Returns:
      the number of variables.

    • sample

      double[] sample()
      Generates a random value vector sampled from this distribution.
      Returns:
      a random value vector.

    • sample

      double[][] sample(int sampleSize) throws MathIllegalArgumentException
      Generates a list of a random value vectors from the distribution.
      Parameters:
      sampleSize - the number of random vectors to generate.
      Returns:
      an array representing the random samples.
      Throws:
      MathIllegalArgumentException - if sampleSize is not positive.
      See Also: