Constructor Detail

• MixtureMultivariateRealDistribution

  public MixtureMultivariateRealDistribution(List<Pair<Double,T>> components)

  Creates a mixture model from a list of distributions and their associated weights.

  Note: this constructor will implicitly create an instance of Well19937c as random generator to be used for sampling only (see sample() and AbstractMultivariateRealDistribution.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:

  components - List of (weight, distribution) pairs from which to sample.

• MixtureMultivariateRealDistribution

  public MixtureMultivariateRealDistribution(RandomGenerator rng,
                                     List<Pair<Double,T>> components)

  Creates a mixture model from a list of distributions and their associated weights.

  Parameters:

  rng - Random number generator.

  components - Distributions from which to sample.

  Throws:

  NotPositiveException - if any of the weights is negative.

  DimensionMismatchException - if not all components have the same number of variables.

Method Detail

• density

  public double density(double[] values)

  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:

  values - Point at which the PDF is evaluated.

  Returns:

  the value of the probability density function at point x.

• sample

  public double[] sample()

  Generates a random value vector sampled from this distribution.

  Specified by:

  sample in interface MultivariateRealDistribution

  Specified by:

  sample in class AbstractMultivariateRealDistribution

  Returns:

  a random value vector.

• reseedRandomGenerator

  public void reseedRandomGenerator(long seed)

  Reseeds the random generator used to generate samples.

  Specified by:

  reseedRandomGenerator in interface MultivariateRealDistribution

  Overrides:

  reseedRandomGenerator in class AbstractMultivariateRealDistribution

  Parameters:

  seed - Seed with which to initialize the random number generator.

• getComponents

  public List<Pair<Double,T>> getComponents()

  Gets the distributions that make up the mixture model.

  Returns:

  the component distributions and associated weights.