org.apache.commons.math3.distribution

## Interface MultivariateRealDistribution

- All Known Implementing Classes:
    AbstractMultivariateRealDistribution, MixtureMultivariateNormalDistribution, MixtureMultivariateRealDistribution, MultivariateNormalDistribution

      public interface MultivariateRealDistribution

  Base interface for multivariate distributions on the reals. 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.
  Since:
    3.1

- - ### Method Summary

    Methods
    Modifier and Type | Method and 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 Detail

    - #### 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 NotStrictlyPositiveException

      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:
        `NotStrictlyPositiveException` - if `sampleSize` is not positive.
      See Also:
        `sample()`

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