Interface MultivariateDistribution

All Superinterfaces:
Serializable
All Known Implementing Classes:
MultivariateExponentialFamilyMixture, MultivariateGaussianDistribution, MultivariateGaussianMixture, MultivariateMixture
public interface MultivariateDistribution extends Serializable
Probability distribution of multivariate random variable.
See Also:

  • Method Summary

    Modifier and Type
    Method
    Description
    double
    cdf(double[] x)
    Cumulative distribution function.
    DenseMatrix
    cov()
    The covariance matrix of distribution.
    double
    entropy()
    Shannon's entropy of the distribution.
    int
    length()
    The number of parameters of the distribution.
    default double
    likelihood(double[][] x)
    The likelihood of the sample set following this distribution.
    default double
    logLikelihood(double[][] x)
    The log likelihood of the sample set following this distribution.
    double
    logp(double[] x)
    The density at x in log scale, which may prevents the underflow problem.
    double[]
    mean()
    The mean vector of distribution.
    double
    p(double[] x)
    The probability density function for continuous distribution or probability mass function for discrete distribution at x.

  • Method Details

    • length

      int length()
      The number of parameters of the distribution. The "length" is in the sense of the minimum description length principle.
      Returns:
      the number of parameters of the distribution.

    • entropy

      double entropy()
      Shannon's entropy of the distribution.
      Returns:
      Shannon entropy

    • mean

      double[] mean()
      The mean vector of distribution.
      Returns:
      the mean vector.

    • cov

      DenseMatrix cov()
      The covariance matrix of distribution.
      Returns:
      the covariance matrix.

    • p

      double p(double[] x)
      The probability density function for continuous distribution or probability mass function for discrete distribution at x.
      Parameters:
      x - a real vector.
      Returns:
      the desnity.

    • logp

      double logp(double[] x)
      The density at x in log scale, which may prevents the underflow problem.
      Parameters:
      x - a real vector.
      Returns:
      the log density.

    • cdf

      double cdf(double[] x)
      Cumulative distribution function. That is the probability to the left of x.
      Parameters:
      x - a real vector.
      Returns:
      the probability.

    • likelihood

      default double likelihood(double[][] x)
      The likelihood of the sample set following this distribution.
      Parameters:
      x - a set of samples.
      Returns:
      the likelihood.

    • logLikelihood

      default double logLikelihood(double[][] x)
      The log likelihood of the sample set following this distribution.
      Parameters:
      x - a set of samples.
      Returns:
      the log likelihood.